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The use of a static modulation coding scheme (MCS), such as 7, and resource keep probability ( P r k ) value, such as 0.8, was proven to be insufficient to achieve the best packet reception ratio (PRR) performance. Various adaptation techniques have been used in the following years. This work introduces a novel optimization algorithm approach called the fuzzy inference reinforcement learning (FIRL) sequence for adaptive parameter configuration in cellular vehicle-to-everything (C-V2X) mode-4 communication networks. This innovative method combines a Sugeno-type fuzzy inference system (FIS) control system with a Q-learning reinforcement learning algorithm to optimize the PRR as the key metric for overall network performance. The FIRL sequence generates adaptive configuration parameters for P r k and MCS index values each time the Long-Term Evolution (LTE) packet is generated. Simulation results demonstrate the effectiveness of this optimization algorithm approach, achieving up to a 169.83% improvement in performance compared to static baseline parameters. [ABSTRACT FROM AUTHOR]

We investigate the peak-power limited (PPL) Additive White Gaussian Noise (AWGN) channels in which the signal is band-limited, and its instantaneous power cannot exceed the power P. This model is relevant to many communication systems; however, its capacity is still unknown. We use a new geometry-based approach which evaluates the maximal entropy of the transmitted signal by assessing the volume of the body, in the space of Nyquist-rate samples, comprising all the points the transmitted signal can reach. This leads to lower bounds on capacity which are tight at high Signal to Noise Ratios (SNRs). We find lower bounds on capacity, expressed as power efficiency, that were higher than the known ones by a factor of 3.3 and 8.6 in the low-pass and the band-pass cases, respectively. The gap to the upper bounds is reduced to a power ratio of 1.5. The new bounds are numerically evaluated for FDMA-style signals with limited duration and also are derived in the general case as a conjecture. The penalty in power efficiency due to the peak power constraint is roughly 6 dB at high SNRs. Further research is needed to develop effective modulation and coding for this channel. [ABSTRACT FROM AUTHOR]

Compared with the amplitude modulation of conventional interrupted sampling repeater jamming (ISRJ), the image feature control method based on phase modulation exhibits greater energy efficiency and, therefore, has received wide attention recently. In this paper, an Inverse Synthetic Aperture Radar (ISAR) image feature suppression method based on arbitrary phase encoding (APE) is proposed. The parameter design criterion is further analyzed. Through the nonperiodic segmented coding and modulation of the imaging signal in fast and slow time domains, the modulated signal produces a two-dimensional suppression region with uniform energy distribution in the ISAR image. Simulations via the measured Yak-42 aircraft data have verified the effectiveness of the proposed method for target feature control. Compared to binary phase modulation jamming, the APE method with a phase modulation accuracy of 1 degree can achieve the same jamming effect while reducing the jamming power requirement by 3 dB. By optimizing with the proposed method, the image entropy of the interfered image increases by 1.1 to 1.5 compared to the original image. [ABSTRACT FROM AUTHOR]

The active materials-loaded reconfigurable metasurface is a potential platform for terahertz (THz) communication systems. However, the requirements of the modulation performance and the modulation rate put forward the opposite requirements on the excited conductivity of active materials. In this paper, we proposed a concept for a metal-doped active material switch that can produce an equivalent high excited conductivity while reducing the required threshold of the active material conductivity, thus balancing the conflict between the two mutual requirements. Based on it, we designed a reconfigurable electromagnetically induced transparency (EIT) metasurface driven by a low excited conductivity of vanadium dioxide  VO 2 , which can achieve the amplitude modulation and amplitude coding under the control of light and electric. Simulation results validate the role of the metal-doped  VO 2  switch on the metasurface. This work provides a new scheme to mediate the contradiction between the modulation performance and the modulation rate in the requirement of active material's excited conductivity, which facilitates the development of new terahertz modulators based on reconfigurable metasurfaces. In addition, the concept of a metal-doped active material switch will also provide a solution to the limitations of active material from the design layer. [ABSTRACT FROM AUTHOR]

The rapid developments of 5G and B5G networks have posed higher demands on retransmission in certain scenarios. This article reviews classical finite-length coding performance prediction formulas and proposes rate prediction formulas for coded modulation retransmission scenarios. Specifically, we demonstrate that a recently proposed model for correcting these prediction formulas also exhibits high accuracy in coded modulation retransmissions. To enhance the generality of this model, we introduce a range variable P final to unify the predictions with different SNRs. Finally, based on simulation results, the article puts forth recommendations specific to retransmission with a high spectral efficiency. [ABSTRACT FROM AUTHOR]

The integration of information and communication technologies in the field of healthcare has generated a positive transformation in the traditional way of providing patient care, optimizing medical services, and streamlining healthcare operations. Traditionally, healthcare systems have relied on radio frequency (RF) signals for data transmission. However, the conventional RF wireless network faces ever-increasing challenges, such as spectrum shortage and a congested frequency spectrum. Moreover, issues such as interference, security vulnerabilities, and potential health risks associated with prolonged exposure to RF electromagnetic radiation complicate its application in healthcare environments. To address these challenges, visible light communication (VLC) systems, which offer dual functionalities, data transmission, and illumination, have emerged as a promising complementary solution to traditional RF-based options. VLC provides secure, high-speed data communication that is immune to RF interference, making it particularly suitable for healthcare settings. This research examines the advancements in e-health systems that utilize VLC technology, considering various modulation and channel coding techniques, with a focus on evaluating the effectiveness and limitations of these techniques to determine their impact on overall performance. [ABSTRACT FROM AUTHOR]

In response to the challenge of existing wireless communication anti-jamming methods in effectively handling unknown jamming, this paper proposes a multi-parameter control anti-jamming algorithm for wireless communication systems based on the Linear–Quadratic Regulator (LQR). First, the proposed algorithm models the wireless communication system as a linear switched system based on the modulation and coding scheme. Subsequently, a feedback controller design method based on the LQR is introduced. By utilizing the multiple Lyapunov function method combined with linear matrix inequalities, sufficient criteria for the asymptotic stability of the system under unknown jamming conditions are provided. Finally, theoretical analysis and simulation results indicate that the proposed algorithm can rapidly adjust modulation and coding schemes as well as transmission power in complex jamming environments, thereby maintaining bit error rate (BER) stability and enhancing the reliability of the communication system. [ABSTRACT FROM AUTHOR]

Waveform design for integrated radar and jamming is generally based on the concept of shared waveform, which uses jamming signals without typical radar signal characteristics for detection. Existing waveforms have shown limited design flexibility, high levels of sidelobe in detection results, and overall ordinary performance. We propose an integrated radar and jamming waveform based on smart modulation and complementary coding. Unlike traditional integrated radar and jamming waveform based on smart modulation, the phase angle of the binary phase-coded sequence is adjustable in this smart modulation method, allowing for a controllable jamming effect, achieving true smart modulation. However, this smart modulation waveform also suffers from high sidelobes in detection. To address this issue, we take a complementary coding approach and design a smart modulation waveform with complementary characteristics. This waveform can synthesize a complete linear frequency modulation (LFM) signal by adding two pulses together, thereby reducing the sidelobes in the smart modulation waveform and enhancing its detection performance. Theoretical analysis indicates that the detection and jamming effects of this integrated waveform can be flexibly controlled by adjusting the phase angles of the coding sequences. Simulation analysis and experimental results confirm the significant advantages of this waveform. [ABSTRACT FROM AUTHOR]

In this paper, a subset-optimized eight-dimensional trellis-coded quadrature amplitude modulation (SO-8DTCM-16QAM) format for higher-order constellations in high-speed optical communications is proposed. This scheme increases the number of subsets of base 2D constellation divisions. On this basis, it is further optimized by using 2D subsets for Cartesian product combinations to obtain 4D subsets and eliminate the combinations with small Euclidean distances. Finally, the 4D subsets are utilized to construct interrelated 8D subsets for trellis coding modulation and signal transmission. The proposed scheme can effectively reduce the decoding complexity and outperforms the conventional scheme at a high signal-to-noise ratio (SNR). Simulation verification of the proposed scheme is carried out, and the results show that the SO-8DTCM-16QAM achieves signal-to-noise ratio (SNR) gains of 1.60 dB, 1.56 dB, 1.51 dB, and 1.33 dB, respectively, compared with the conventional 8D-16QAM signals when BTB and 5/20/30 km optical signal transmission are performed. The SO-8DTCM-16QAM also achieves an SNR gain of 1.86 dB, 1.75 dB, and 1.22 dB at a net transmission rate of 14/21/28 GBaud. In addition, the SO-8DTCM-16/32/64QAM achieves an SNR gain of 1.27 dB, 0.80 dB, and 1.24 dB, respectively, when compared with the unoptimized 8DTCM-16/32/64QAM. Meanwhile, the proposed eight-subset SO-8DTCM-QAM scheme reduces the complexity of the decoding computation in the subset selection part and the constellation point selection part by 93.75% and 50%, respectively, compared with the unoptimized eight-subset and four-subset 8DTCM-QAM schemes. It can be seen that the proposed scheme simultaneously optimizes the transmission performance and complexity of high-speed optical communication systems and has practical application value. [ABSTRACT FROM AUTHOR]

Flying base stations, also known as aerial base stations, provide wireless connectivity to the user and utilize their aerial mobility to improve communication performance. Flying base stations depend on traditional stationary terrestrial base stations for connectivity, as stationary base stations act as the gateway to the backhaul/cloud via a wired connection. We introduce the flying base station channel capacity to build on the Shannon channel capacity, which quantifies the upper-bound limit of the rate at which information can be reliably transmitted using the communication channel regardless of the modulation and coding techniques used. The flying base station's channel capacity assumes aerial mobility and ideal positioning for maximum channel capacity. Therefore, the channel capacity limit holds for any digital and signal processing technique used and for any location or positioning of the flying base station. Because of its inherent reliance on the stationary terrestrial base station, the flying base station channel capacity depends on the stationary base station's parameters, such as its location and SNR performance to the user, in contrast to previous research, which focused on the link between the user and the flying base station without the stationary base station. For example, the beneficial region (where there is a positive flying base station capacity gain) depends on the stationary base station's power and channel SNR in addition to the flying base station's own transmission power and whether it has full duplex vs. half-duplex capability. We jointly study the mobility and the wireless communications of the flying base station to analyze its position, channel capacity, and beneficialness over the stationary terrestrial base station (capacity gain). As communication protocols and implementations for flying base stations undergo development for next-generation wireless networking, we focus on information-theoretical analyses and channel capacity to inform future research and development in flying base station networking. [ABSTRACT FROM AUTHOR]

In this paper, a novel data transmission scheme, interference perceptual multi-modulation (IP-MM), is proposed for full-duplex (FD) systems. In order to unlink the conventional uplink (UL) data transmission using a single modulation and coding scheme (MCS) over the entire assigned UL bandwidth, IP-MM enables the transmission of UL data channels based on multiple MCS levels, where a different MCS level is applied to each subband of UL transmission. In IP-MM, a deep convolutional neural network is used for MCS-level prediction for each UL subband by estimating the potential residual self-interference (SI) according to the downlink (DL) resource allocation pattern. In addition, a subband-based UL transmission procedure is introduced from a specification point of view to enable IP-MM-based UL transmission. The benefits of IP-MM are verified using simulations, and it is observed that IP-MM achieves approximately 20 % throughput gain compared to the conventional UL transmission scheme. [ABSTRACT FROM AUTHOR]

Overlapped Time Domain Multiplexing (OvTDM) is a high-rate transmission technology that employs the idea of superposition coded modulation (SCM) scheme for signal generation, aiming to achieve maximum channel capacity sharing. Meanwhile, it is also widely considered as a promising technique toward physical layer security. As a main drawback of such system, a high peak-to-average power ratio (PAPR) issue in this system, arising from multi-layer superposition, can be addressed through intentional clipping. However, the detection at the receiver side is vulnerable to nonlinear distortion caused by clipping, which can degrade the performance. To mitigate this distortion, this paper proposed an iterative scheme for estimating and partially canceling clipping distortion at the receiver. We managed to mitigate the impact of clipping noise as much as possible and minimize the cost of optimizing PAPR, thereby improving the transmission performance of OvTDM in the context of amplitude clipping. [ABSTRACT FROM AUTHOR]

With the rapid deployment of intelligent transportation systems in real-life applications, both dedicated short-range communications (DSRC) and cellular Vehicle-to-Everything (C-V2X), utilized to enable V2X communication, are undergoing extensive development to meet the quality of service (QoS) demands of advanced vehicular applications and scenarios. Compared to C-V2X, which lacks fully validated effective reliability, DSRC has undergone extensive field testing worldwide, ensuring its practicality. IEEE 802.11bd, as the next-generation V2X (NGV) standard within DSRC, is expected to greatly exceed the performance of its predecessor, 802.11p. However, existing studies mention that the ambient traffic environment will influence the performance of V2X due to the cyber-physical properties of V2X. To fully assess the advancements of NGV, this study presents a comparative analysis of IEEE 802.11bd and IEEE 802.11p, focusing on dynamic traffic conditions. Specifically, the technical advancements of the IEEE 802.11bd standard are first theoretically examined, emphasizing significant enhancements in aspects like modulation and coding schemes, coding rates, and channel coding. Subsequently, these critical technical enhancements are implemented in Veins, a simulation framework for the Internet of Vehicles (IoV), encompassing large-scale dynamic traffic scenarios. The simulation results indicate that the IEEE 802.11bd standard significantly enhances the data transfer rate compared to IEEE 802.11p, achieving a stable twofold increase. Furthermore, the data transmission latency is reduced by over half compared to IEEE 802.11p, while the data transmission reliability experiences a noteworthy 20% enhancement. Notably, the enhanced data transmission mode of the IEEE 802.11bd standard requires an increased signal-to-noise ratio (SNR). Additionally, this research evaluates the data dissemination properties in the IoV and finds that the traffic volume has a limited impact on the data propagation speed. [ABSTRACT FROM AUTHOR]

Labeling-Based Recipient Identification (LABRID) brings the possibility of representing the destination station address in a Bit-Interleaved Coded Modulation with Iterative Decoding (BICM-ID) system by a signal labeling rule. Low-order modulations, such as BPSK or QPSK, pose a general problem for BICM-ID due to a limited convergence of iterative decoding. In the context of LABRID, they have one more drawback—a small number of different labeling rules in general; the number of the optimal ones, which exhibit the maximal asymptotic coding gain, is reduced even further. Meanwhile, LABRID needs a sizable collection of different optimal labeling rules to serve many users in large wireless networks. In this paper, the author suggests the use of hypercube BPSK or QPSK labeling to overcome all these challenges. By means of the Reactive Tabu Search (RTS) algorithm, more than 1500 equivalent optimal hypercube labeling rules are found. Analytical error bounds of the system are developed and supported by simulation experiments. Then, the focus is moved to the criterion to determine the frame destination at the LABRID receiver; a simple threshold-based method is proposed to keep the incorrect decision probability below 10 − 5 . Finally, it is shown that LABRID outperforms a reference BICM-ID system in terms of computational complexity. [ABSTRACT FROM AUTHOR]

The growing demand for communication technology capable of providing high transmission rates in maritime environments has led to the exploration of the very high frequency (VHF) data exchange system (VDES) as a promising solution. The VDES, the integration of an automatic identification system (AIS), application-specific messaging (ASM), and VHF data exchange (VDE), offers improved transmission rates and stable connections compared with existing technologies. Although the VDES supports high transmission rates through various modulation and coding scheme (MCS) technologies, it lacks a standardized mechanism for controlling MCS parameters and relies on user algorithms for operation. In this paper, we introduce the maritime auto-rate fall-back (mARF) technology, designed to effectively address the challenges of maritime communication scenarios using the MCS framework provided by the VDES. mARF technology incorporates fast drop-out and recovery mechanisms to swiftly adapt to changing MCS types in the presence of deep nulls, a common occurrence in maritime communication environments. These adaptive thresholds for fast drop-out and recovery operations are dynamically learned using historical communication data. Through extensive simulations, we demonstrate the effectiveness of mARF in enhancing the MCS control capabilities of the VDES. Our results show a significant performance improvement of 18% compared to the existing model, validating the potential of mARF in optimizing maritime communication channels and supporting a high transmission rate. [ABSTRACT FROM AUTHOR]

A high-frequency surface wave radar (HFSWR) is the only sensor that provides inexpensive surveillance for up to 200 nautical miles (NM) of the exclusive economic zone in the 3–5 MHz band. However, because of its long wavelength, its angular resolution is low. Multiple-input multiple-output (MIMO) technology is an attractive method to improve angular resolution. This paper proposes MIMO waveforms and their processing that can be used in HFSWR systems. This dual modulation method applies linear frequency modulation to each pulse and orthogonal polyphase codes for a few consecutive pulses to enable MIMO processing. The proposed method can effectively remove the correlation of mutual interference and exhibits excellent performance in removing multiple-time-around echoes. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive bit-interleaved polar coded modulation (A-BIPCM) method based on minimum logarithmic upper bound weight (MLUW). It is designed to reduce the fading effects and long string of bit error interference caused by atmospheric turbulence in free-space optical communications (FSOC). To assess the effectiveness of this method across turbulent channels of varying intensities, we conducted an evaluation of the bit error rate (BER) performance of polar codes in turbulent channels. The results demonstrate significant performance improvements provided by the A-BIPCM method compared to conventional polar code encoding and decoding. Specifically, under weak, moderate, and strong turbulence conditions, the A-BIPCM method achieves performance gains of 0.96 dB, 1.66 dB, and 1.35 dB, respectively. Additionally, an experimental verification platform for FSOC employing intensity modulation direct detection (IM/DD) with an atmospheric turbulence simulation channel, is established in this work. When the optical power of the detector is −16 dBm, the traditional polar code encoding and decoding performance at BER = 2.36 × 10−5, whereas the A-BIPCM scheme exhibits a significantly higher performance at BER = 2.11 × 10−6. The BER has been improved by representing an order of magnitude. [ABSTRACT FROM AUTHOR]

This paper addresses the escalating threat of malicious jamming in next-generation communication systems, propelled by their continuous advancement in speed, latency, and connectivity. Recognizing the imperative for communication security, we propose an efficient jamming detection method with distinct innovations and contributions. Motivated by the growing sophistication of jamming techniques, we advocate the adoption of the error vector magnitude (EVM) metric, measured in IQ symbols, deviating from traditional received signal strength and bit error rate-based measurements. Our method achieves enhanced jamming detection sensitivity, surpassing existing approaches. Furthermore, it introduces low complexity, ensuring resource-effective detection. Crucially, our approach provides vital jammer frequency information, enhancing counteraction capabilities against jamming attacks. It demonstrates stable results against varying system parameters, such as modulation type and code rate, thereby contributing to adaptability. Emphasizing practicality, the method seamlessly integrates into 5G and LTE systems without imposing additional overhead. Versatility is demonstrated through successful operations in diverse scenarios that are run by extended simulation conditions. Theoretical analysis substantiates these advantages, reinforcing the validity of our methodology. The study's success is further validated through laboratory experiments, providing empirical evidence of its effectiveness. The proposed method represents a significant step toward fortifying next-generation communication systems against evolving jamming threats. [ABSTRACT FROM AUTHOR]

WiFi is a widely used wireless technology for data transmission. WiFi can also play a crucial role in simultaneously broadcasting content to multiple devices in multimedia transmission for venues such as classrooms, theaters, and stadiums, etc. Broadcasting allows for the efficient dissemination of information to all devices connected to the network, and it becomes crucial to ensure that the WiFi network has sufficient capacity to transmit broadcast multimedia content without interruptions or delays. However, using WiFi for broadcasting presents challenges that can impact user experience, specifically the difficulty of obtaining real-time feedback from potentially hundreds or thousands of users due to potential collisions of feedback messages. This work focuses on providing accurate feedback to the Access Point about the percentage of users not receiving broadcast traffic correctly so it can adjust its Modulation and Coding Scheme (MCS) while transmitting broadcast multimedia content to many users. The proposed method is comprised of two sequential algorithms. In order to reduce the probability of a collision after transmitting each message, an algorithm searches for the best probability value for users to transmit ACK/NACK messages, depending on whether messages are received correctly or not. This feedback allows the Access Point to estimate the number of STAs correctly/incorrectly receiving the messages being transmitted. A second algorithm uses this estimation so the Access Point can select the best MCS while maintaining the percentage of users not receiving broadcast content correctly within acceptable margins, thus providing users with the best possible content quality. We implemented the proposed method in the ns-3 simulator, and the results show it yields quick, reliable feedback to the Access Point that was then able to adjust to the best possible MCS in only a few seconds, regardless of the user density and dimensions of the scenario. [ABSTRACT FROM AUTHOR]

Reinforcement Learning (RL) has been employed to assign transmission parameters to all sub-carriers in a set frequency band for anti-jamming Orthogonal Frequency Division Multiplexing (OFDM) systems. However, prior works often overlooked the influence of wireless environment fading and convergence issues stemming from overly large parameter sets. To address these challenges, an anti-jamming scheme was proposed based on the Non-Contiguous Orthogonal Frequency Division Multiplexing (NC-OFDM) communication system integrated with reinforcement learning. First, all sub-carriers were divided into sub-bands, and a Finite State Markov Sub-bands (FSMS) model was established to describe the time-varying fading characteristics of each sub-band by combining Adaptive Modulation and Coding (AMC) technology. To mitigate instability due to the fading channel, a joint sub-band and modulation anti-jamming decision scheme was adopted, enabling the transmitter to select the optimal sub-band and transmission rate. Ultimately, this decision-making process was modeled as a Markov Decision Process (MDP), and an Upper Confidence Bound based Q-learning (UCB-Q) anti-jamming algorithm was proposed for obtaining the joint sub-band and transmission rate selection strategies. Simulation results indicate that the proposed algorithm demonstrates enhanced speed and superior average throughput. Additionally, the algorithm showcases the same commendable anti-jamming performance in scenarios with time-varying dynamic jamming. [ABSTRACT FROM AUTHOR]

The modulation coding scheme (MCS) index is the essential configuration parameter in cellular vehicle-to-everything (C-V2X) communication. As referenced by the 3rd Generation Partnership Project (3GPP), the MCS index will dictate the transport block size (TBS) index, which will affect the size of transport blocks and the number of physical resource blocks. These numbers are crucial in the C-V2X resource management since it is also bound to the transmission power used in the system. To the authors' knowledge, this particular area of research has not been previously investigated. Ultimately, this research establishes the fundamental principles for future studies seeking to use the MCS adaptability in many contexts. In this work, we proposed the application of the reinforcement learning (RL) algorithm, as we used the Q-learning approach to adaptively change the MCS index according to the current environmental states. The simulation results showed that our proposed RL approach outperformed the static MCS index and was able to attain stability in a short number of events. [ABSTRACT FROM AUTHOR]

The design of transmitting waveforms is an effective way to improve the detection performance of sonar systems. For the problem of high-range sidelobe when designing reverberation-resistant waveforms, this paper proposes a high-resolution wideband composite waveform design with reverberation suppression performance and a waveform parameter improvement method. Firstly, we propose a novel wideband waveform, which utilizes linear frequency modulation (LFM) as the fundamental pulse, referred to as multi-parameter coded modulation LFM pulse (MPCM-LFM). Additionally, we deduce the wideband ambiguity function for waveform design. Then, we deduce the constraint relations of the waveform parameters for different sub-band overlaps, and according to the mathematical expressions of the obtained range ambiguity function, we analyze in detail the effects of the waveform parameters on the range ambiguity function under different constraints. Secondly, on the basis of the analysis, we also propose a hopping carrier frequency constraint rule to optimize the spectral performance, and the range sidelobe is restrained effectively in significant measure by this parameter improvement method. Finally, we analyze the computer simulation results. It is obvious that our proposed waveform parameter improvement method leads to good results. The proposed improved MPCM-LFM signal shows a "near-thumbtack" ambiguity function, whose sidelobe suppression performance is superior to other classical waveforms in the desired region, and it can realize high-precision parameter estimation. In addition, the proposed improved MPCM-LFM signal possesses good performance in detecting stationary and low Doppler targets in the background of reverberation. [ABSTRACT FROM AUTHOR]

The concept of cognitive radio (CR) as a tool to optimize the obstacle of spectral coexistence has promoted the development of shared satellite–terrestrial wireless networks. Nevertheless, in some applications like Earth Exploration Satellite Services, which demand high spectral efficiency (bps/Hz) for downlink transmissions, spectral coexistence amidst interferences from cellular Base Stations is still challenging. Our research aims to mitigate these interferences on low-orbit satellite downlinks carrying imaging data received from a ground station. In order to fulfill this, we present cognitive radio approaches to enhance spectrum exploitation and introduce the adaptive modulation and coding (MODCOD) technique to increase RF power and spectral efficiencies. Therefore, we propose a combined methodology using CR and adaptive MODCOD (ACM) techniques. Afterwards, we applied the solution by monitoring the signal to interference plus noise ratio and the MODCOD strategy. Finally, we provide a real in situ case study at the Cuiabá ground station located in Brazil's central area, which receives images from an Earth observation satellite (EOS). In addition to demonstrating the strategy effectiveness in this scenario, we conducted a bench test emulating the interfering wireless communication system. In this sense, we demonstrated the proposed approach, successfully mitigating the harmful effects on the received EOS images. [ABSTRACT FROM AUTHOR]

Site diversity is the most effective way to recover a signal lost during heavy downpours, especially in tropical regions since other mitigation techniques such as adaptive power control and code modulation may be unreliable during such. Duplicated links at diverse sites are deployed, and the least-attenuated signal of either site will be routed to the prime site for further operation. Since the deployment is costly, a diversity-gain model is used to estimate the appropriateness of selected sites. Diversity gain is known to depend on site-separation distance and elevation angle and, optionally, baseline angle and signal frequency, based on the region of research. In addition to these factors, the horizontal rain-cell span and the wind's impact on the gain are ongoing investigations, especially in tropical regions. This article presented the rain analysis from the year 2014 to mid-July 2017 at eight sites in the Gombak and Sepang districts of Malaysia to investigate the dependency relevancies. The rain rates were then used to predict the attenuation using the ITU-R P.618-13 rain-attenuation model, and the inter- and cross-district gain characteristics were evaluated. The observation of diurnal rain during the northeast seasons yielded that the northeast wind stimulates intense rain at locations along its direction, thus, extending the horizontal rain-cell span to 15 km distant from a host. Meanwhile, sites located at 5 km distant, slightly perpendicular to the wind direction, and from 90° to 180° from due north of the host, experience less rain. The baseline angle variation establishes nonimpact to the gain and lengthening the site-separation distance presented equal chances to the shorter span towards diversity-gain increment. The research outcome is necessary to formulate a more reliable diversity-gain model to be used in the industry. [ABSTRACT FROM AUTHOR]

Herein, we propose the use of the logarithmic values of data transmission rates for multi-armed bandit (MAB) algorithms that adjust the modulation and coding scheme (MCS) levels of data packets in carrier-sensing multiple access/collision avoidance (CSMA/CA) wireless networks. We argue that the utilities of the data transmission rates of the MCS levels may not be proportional to their nominal values and suggest using their logarithmic values instead of directly using their data transmission rates when MAB algorithms compute the expected throughputs of the MCS levels. To demonstrate the effectiveness of the proposal, we introduce two MAB algorithms that adopt the logarithmic rates of the transmission rates. The proposed MAB algorithms also support frame aggregations available in wireless network standards that aim for a high throughput. In addition, the proposed MAB algorithms use a sliding window over time to adapt to rapidly changing wireless channel environments. To evaluate the performance of the proposed MAB algorithms, we used the event-driven network simulator, ns-3. We evaluated their performance using various scenarios of stationary and non-stationary wireless network environments including multiple spatial streams and frame aggregations. The experiment results show that the proposed MAB algorithms outperform the MAB algorithms that do not adopt the logarithmic transmission rates in both the stationary and non-stationary scenarios. [ABSTRACT FROM AUTHOR]

Using the source residual redundancy in a joint source and channel coded modulation (JSCCM) system to achieve a shaping gain has proven to be a good solution for probabilistic amplitude shaping. In a JSCCM system, rate-compatible source codes are essential for adapting to dynamically changing source probabilities. However, conventional rate-compatible source codes are not appropriate for JSCCM systems, since they may yield a loss in the shaping gain. Moreover, a code design that depends solely on the source decoding threshold appears to be ill suited, thus complicating the search for good source codes. In this paper, we propose a rate-compatible family of source codes for JSCCM systems based on an achievable system rate analysis and the source protograph extrinsic information transfer (PEXIT) algorithm. The proposed codes not only have good source decoding thresholds but also obtain shaping gains over the whole considered range of source probabilities. Numerical results show that the proposed rate-compatible family of source codes can significantly improve the bit-error-rate (BER) performance of the JSCCM system. [ABSTRACT FROM AUTHOR]

As the number of Internet of things (IoT) devices increases exponentially, scheduling and managing the radio resources for IoT devices has become more important. To efficiently allocate radio resources, the base station (BS) needs the channel state information (CSI) of devices every time. Hence, each device needs to periodically (or aperiodically) report its channel quality indicator (CQI) to the BS. The BS determines the modulation and coding scheme (MCS) based on the CQI reported by the IoT device. However, the more a device reports its CQI, the more the feedback overhead increases. In this paper, we propose a long short-term memory (LSTM)-based CQI feedback scheme, where the IoT device aperiodically reports its CQI relying on an LSTM-based channel prediction. Additionally, because the memory capacity of IoT devices is generally small, the complexity of the machine learning model must be reduced. Hence, we propose a lightweight LSTM model to reduce the complexity. The simulation results show that the proposed lightweight LSTM-based CSI scheme dramatically reduces the feedback overhead compared with that of the existing periodic feedback scheme. Moreover, the proposed lightweight LSTM model significantly reduces the complexity without sacrificing performance. [ABSTRACT FROM AUTHOR]

To achieve high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) images, this paper focuses on resolving the problem of separating range-ambiguous echoes with the space–time coding (STC) array. At the modeling stage, the transmit elements and pulses of the STC array are configured with time delay and phase coding modulation, which introduces extra degrees of freedom (DOFs) in the transmit domain. To separate the echoes corresponding to different range-ambiguity regions, the equivalent transmit beamforming is performed in the two-dimensional space–frequency domain. Moreover, in order to compensate for the loss of range resolution during the beamforming progress, the frequency splicing method is proposed. At the analysis stage, the distributed target simulation is provided to demonstrate the effectiveness of obtaining HRWS SAR images in the STC radar. Additionally, the performance of resolving range ambiguity is compared with the traditional radar in terms of the range-ambiguity-to-signal ratio (RASR). [ABSTRACT FROM AUTHOR]

Underwater acoustic (UWA) communications face many challenges, such as large multipath delay, severe fading and the time-varying distortions. Chaotic modulations have shown advantages in UWA communications, but the reliability of current chaotic modulations is still not guaranteed. In this paper, a short-length protograph low-density parity-check (P-LDPC) code design framework for the differential chaotic bit-interleaved coded modulation (DC-BICM) system for UWA communication is proposed. This design framework, considering the requirements of short codes in UWA communications, integrates the DC-BICM system, UWA channel and the differential evolutionary code searching algorithm. Through this design framework, the optimized short P-LDPC code can be obtained. Simulation results show that the DC-BICM system with the proposed P-LDPC code can obtain more than 0.48 dB coding gain and reduce 32.6%~69.5% of the average number of iterations compared with the counterparts. Moreover, the reconstructed underwater image with the proposed P-LDPC code is clearest with the highest peak-signal-noise ratio value when compared with counterparts. [ABSTRACT FROM AUTHOR]

By using the residual source redundancy to achieve the shaping gain, a joint source-channel coded modulation (JSCCM) system has been proposed as a new solution for probabilistic amplitude shaping (PAS). However, the source and channel codes in the JSCCM system should be designed specifically for a given source probability to ensure optimal PAS performance, which is undesirable for systems with dynamically changing source probabilities. In this paper, we propose a new shaping scheme by optimizing the bit-labeling of the JSCCM system. Instead of the conventional fixed labeling, the proposed bit-labelings are adaptively designed according to the source probability and the source code. Since it is simple to switch between different labelings according to the source probability and the source code, the proposed design can be considered as a promising low complexity alternative to obtain the shaping gain for sources with different probabilities. Numerical results show that the proposed bit-labelings can significantly improve the bit-error rate (BER) performance of the JSCCM system. [ABSTRACT FROM AUTHOR]

We propose a distributed quasi-cyclic low-density parity-check (QC-LDPC) coded spatial modulation (D-QC-LDPCC-SM) scheme with source, relay and destination nodes. At the source and relay, two distinct QC-LDPC codes are used. The relay chooses partial source information bits for further encoding, and a distributed code corresponding to each selection is generated at the destination. To construct the best code, the optimal information bit selection algorithm by exhaustive search in the relay is proposed. However, the exhaustive-based search algorithm has large complexity for QC-LDPC codes with long block length. Then, we develop another low-complexity information bit selection algorithm by partial search. Moreover, the iterative decoding algorithm based on the three-layer Tanner graph is proposed at the destination to carry out joint decoding for the received signal. The recently developed polar-coded cooperative SM (PCC-SM) scheme does not adopt a better encoding method at the relay, which motivates us to compare it with the proposed D-QC-LDPCC-SM scheme. Simulations exhibit that the proposed exhaustive-based and partial-based search algorithms outperform the random selection approach by 1 and 1.2 dB, respectively. Because the proposed D-QC-LDPCC-SM system uses the optimized algorithm to select the information bits for further encoding, it outperforms the PCC-SM scheme by 3.1 dB. [ABSTRACT FROM AUTHOR]

The concept of labeling-based recipient identification (LABRID) for bit-interleaved coded modulation with iterative decoding (BICM-ID) is revisited. LABRID allows addressing a message recipient station in a wireless network by using an individual labeling map without compromising error performance. This eliminates the need to use any byte of the data frame to carry the recipient address explicitly. In addition, the destination of the frame can be determined in parallel with a BICM-ID decoding procedure in the receiver's physical layer. Therefore, the MAC layer is not involved in processing the vast majority of frames transmitted in a network. Previously, it was shown that LABRID works fine if there are only LABRID-compatible stations within the network, and every receiver can reject frames destined for other receivers. This paper considers a scenario in which LABRID-compatible BICM-ID stations and legacy BICM stations coexist in the same network. A few experiments show that the LABRID receiver can reject an old-fashioned BICM frame by judging the convergence of the iterative decoding process. It also turns out that the legacy BICM receiver can identify and dismiss the LABRID-type frames thanks to the standard cyclic redundancy check (CRC) procedure. [ABSTRACT FROM AUTHOR]

Interrupted sampling repeater jamming (ISRJ) is a classic active coherent jamming. Due to its structural limitations, it has inherent defects such as a discontinuous time–frequency (TF) distribution, strong distribution regularity of pulse compression results, limited jamming amplitude, and strong false targets lagging behind the real target. These defects have not been fully resolved yet due to the limitation of the theoretical analysis system. Based on the analysis of the influence factors of ISRJ on the interference performance for linear-frequency-modulated (LFM) and phase-coded signals, this paper proposes an improved ISRJ method based on the joint subsection frequency shift and two-phase modulation. The coherent superposition of jamming signals at different positions for LFM signals is achieved by controlling the frequency shift matrix and the phase modulation parameters to form a strong pre-lead false target or multiple positions and ranges of blanket jamming areas. For the phase-coded signal, the pre-lead false targets are generated through code prediction and the two-phase modulation of the code sequence, resulting in similar noise interference. The simulation results show that this method can overcome the inherent defects of ISRJ. [ABSTRACT FROM AUTHOR]

The IEEE 802.11ah standard is intended to adapt the specifications of IEEE 802.11 to the Internet of Things (IoT) scenario. One of the main features of IEEE 802.11ah consists of the Restricted Access Window (RAW) mechanism, designed for scheduling transmissions of groups of stations within certain periods of time or windows. With an appropriate configuration, the RAW feature reduces contention and improves energy efficiency. However, the standard specification does not provide mechanisms for the optimal setting of RAW parameters. In this way, this paper presents a grouping strategy based on a genetic algorithm (GA) for IEEE 802.11ah networks operating under the RAW mechanism and considering heterogeneous stations, that is, stations using different modulation and coding schemes (MCS). We define a fitness function from the combination of the predicted system throughput and fairness, and provide the tuning of the GA parameters to obtain the best result in a short time. The paper also includes a comparison of different alternatives with regard to the stages of the GA, i.e., parent selection, crossover, and mutation methods. As a proof of concept, the proposed GA-based RAW grouping is tested on a more constrained device, a Raspberry Pi 3B+, where the grouping method converges in around 5 s. The evaluation concludes with a comparison of the GA-based grouping strategy with other grouping approaches, thus showing that the proposed mechanism provides a good trade-off between throughput and fairness performance. [ABSTRACT FROM AUTHOR]

With the development of the underwater acoustic (UWA) adaptive communication system, energy-efficient transmission has become a critical topic in underwater acoustic (UWA) communications. Due to the unique characteristics of the underwater environment, the transmitter node will almost always have outdated channel state information (CSI), which results in low energy efficiency. In this paper, we take full advantage of bidirectional links and propose an adaptive modulation and coding (AMC) scheme that aims to maximize the long-term energy efficiency of a single link by jointly scheduling the coding rate, modulation order, and transmission power. Considering the complexity characteristics of UWA channels, we proposed a bit error ratio (BER) estimation method based on deep neural networks (DNN). The proposed network could realize channel estimation, feature extraction, and BER estimation by using a fixed pilot of the feedback link. Then, we design a channel classification method based on the estimated BERs of the modulation and coding scheme (MCS) and further model the UWA channels as a finite-state Markov chain (FSMC) with an unknown transition probability. Thus, we formulate the AMC problem as a Markov Decision Process (MDP) and solve it through a reinforcement learning framework. Considering the large state-action pairs, a double deep Q-network (DDQN) based scheme is proposed. Simulation results demonstrate that the proposed AMC scheme outperforms the fixed MCS with a perfect channel information state, and achieves near-optimal energy efficiency. [ABSTRACT FROM AUTHOR]

Link adaptation (LA) matches transmission parameters to conditions on the radio link, and therefore plays a major role in telecommunications. Improving LA is within the requirements for next-generation mobile telecommunication systems, and by refining link adaptation, a higher channel efficiency can be achieved (i.e., an increased data rate thanks to lower required bandwidth). Furthermore, by replacing traditional LA algorithms, radio transmission systems can better adapt themselves to a dynamic environment. There are several drawbacks to current state-of-the-art approaches, including predefined and static decision boundaries or relying on a single, low-dimensional metric. Nowadays, a broadly used approach to handle a variety of related input variables is a neural network (NN). NNs are able to make use of multiple inputs, and when combined with reinforcement learning (RL), the so-called deep reinforcement learning (DRL) approach emerges. Using DRL, more complex parameter relationships can be considered in order to recommend the modulation and coding scheme (MCS) used in LA. Hence, this work examines the potential of DRL and includes experiments on different channels. The main contribution of this work lies in using DRL algorithms for LA, optimized for throughput based on a subcarrier observation matrix and a packet success rate feedback system. We apply Natural Actor-Critic (NAC) and Proximal Policy Optimization (PPO) algorithms on simulated channels with a subsequent feasibility study on a prerecorded real-world channel. Empirical results produced by experiments on the examined channels hint that Deep Reinforcement Learning for Link Adaptation (DRLLA) offers good performance indicated by a promising data rate on the additive white Gaussian noise (AWGN) channel, the non-line-of-sight (NLOS) channel, and a prerecorded real-world channel. No matter the channel impairment, the agent is able to respond to changing signal-to-interference-plus-noise-ratio (SINR) levels, as exhibited by expected changes in the effective data rate. [ABSTRACT FROM AUTHOR]

Featured Application: X-ray phase contrast and dark-field imaging have been recently introduced in conventional systems. They have been demonstrated to outperform the conventional imaging modalities. This article proposes a comprehensive overview of the experimental techniques that allow obtaining these new contrasts on conventional systems. Since the seminal work of Roentgen, X-ray imaging mainly uses the same physical phenomenon: the absorption of light by matter. Thanks to third-generation synchrotrons that provide a high flux of quasi-coherent X-rays, we have seen in recent years new imaging concepts such as phase contrast or dark-field imaging that were later adapted to conventional X-ray sources. These innovative imaging techniques are particularly suitable for visualizing soft matter, such as biological tissues. After a brief introduction to the physical foundations of these two techniques, we present the different experimental set-ups that are now available to produce such contrasts: propagation, analyzer-based, grating interferometry and non-interferometric methods, such as coded aperture and modulation techniques. We present a comprehensive review of their principles; associated data processing; and finally, their requirements for their transfer outside of synchrotrons. In conclusion, gratings interferometry, coded aperture and modulation techniques seem to be the best candidates for the widespread use of phase contrast and dark-field imaging on low-cost X-ray sources. [ABSTRACT FROM AUTHOR]

In bit-patterned media recording (BPMR) systems, the readback signal is affected by neighboring islands that are characterized by intersymbol interference (ISI) and intertrack interference (ITI). Since increasing the areal density encourages the influence of ISI and ITI, it is more difficult to detect the data. Modulation coding can prevent the occurrence of specific data patterns that can cause severe ISI and ITI. In this study, we propose a modulation decoding method based on the K-means algorithm for a BPMR system to improve decoding capabilities. As the K-means algorithm helps understand data patterns and characteristics, the K-means decoder shows the best performance. [ABSTRACT FROM AUTHOR]

We present a well-known generalized Reed–Solomon (GRS) code incorporated with space-time block coded spatial modulation (STBC-SM) for wireless networks, which is capable of enjoying coded cooperation between the source and the relay. In the proposed distributed GRS-coded STBC-SM (DGRSC-STBC-SM) scheme, the source and relay nodes use distinct GRS codes. At the relay, we employ the concept of information selection to choose the message symbols from the source for further encoding. Thus, the codewords jointly constructed by the source and relay are generated at the destination. For achieving the best codeword set at the destination, we propose an optimal algorithm at the relay to select partial symbols from the source. To reduce the computational complexity, we propose a more practical algorithm with low complexity. Monte Carlo simulation results show that the proposed scheme using the low-complexity algorithm can achieve near-optimal error performance. Furthermore, our proposed scheme provides better error performance than its corresponding coded non-cooperative counterpart and the existing Reed–Solomon coded cooperative SM (RSCC-SM) scheme under identical conditions. [ABSTRACT FROM AUTHOR]

Nowadays low Earth orbit (LEO) Earth observation (EO) satellites commonly use constant coding modulation (CCM) or variable coding modulation (VCM) schemes for data transmission to ground stations (G/S). Compared with CCM and VCM, the adaptive coding modulation (ACM) could further improve the data throughput of the link by making full use of link resource and the time-varying characteristics of atmospheric attenuation. In order to comprehensively study the data transmission performance, one new index which could be utilized as a quantitative index for the satellite-to-ground data transmission scheme selection, the transmission efficiency factor (TEF) of LEO satellites is proposed and defined as "the product of the link availability and the average useful data rate". Then, the transmission efficiency of CCM, VCM and ACM at typical G/S with different weather characteristics at Ka-band is compared and analyzed. The results show that ACM is more suitable for the G/S with moderate and abundant rainfall. Compared with the CCM of MCS 28, for Beijing G/S and Sanya G/S, ACM not only improves the transmission efficiency with the TEF increased by 3.62% and 24.51%, respectively, but also improves the link availability with the outage period reduced by 82.47% and 75.18%, respectively. [ABSTRACT FROM AUTHOR]

The Ultra-Reliable Low-Latency Communication (URLLC) is expected to be an important feature of 5G and beyond networks. Supporting URLLC in a resource-efficient manner demands optimal Modulation and Coding Scheme (MCS) selection and spectrum allocation. This paper presents a study on MCS selection and spectrum allocation to support URLLC. The essential idea is to establish an analytical connection between the delay and reliability requirements of URLLC data transmission and the underlying MCS selection and spectrum allocation. In particular, the connection factors in fundamental aspects of wireless data communication include channel quality, coding and modulation, spectrum allocation and data traffic characteristics. With this connection, MCS selection and spectrum allocation can be efficiently performed based on the delay and reliability requirements of URLLC. Theoretical results in the scenario of a 5G New Radio system are presented, where the Signal-to-Noise Ratio (SNR) thresholds for adaptive MCS selection, data-transmission rate and delay, as well as spectrum allocation under different configurations, including data duplication, are discussed. Simulation results are also obtained and compared with the theoretical results, which validate the analysis and its efficiency. [ABSTRACT FROM AUTHOR]

A laser altimeter using code modulation techniques receives a backscattered pulse wider than the transmitted rectangular pulse when scanning a rough or sloped target surface. This leads to degrading the ranging performance in terms of signal-to-noise ratio (SNR) and detection probability. Unlike the pulsed techniques, little work has focused on the pulse broadening effect of the code modulation techniques. In this study, mathematical models were derived to investigate the pulse broadening effect on the ranging performance of a return-to-zero pseudorandom noise (RZPN) laser altimeter. Considering that the impulse response can be approximated by a Gaussian function, the analytical waveform was derived using a new flat-topped multi-Gaussian beam (FMGB) model. The closed-form expressions were also analytically derived for a peak cross-correlation, SNR, and detection probability in terms of the pulse broadening effect. With the use of a three-dimensional model of asteroid Itokawa for practical surface profiles, the analytical expressions were validated by comparing to the results obtained from numerical simulations. It was also demonstrated that the pulse broadening effect dropped down the peak cross-correlation and then deteriorated the ranging performance. These analytical expressions will play an important role in not only designing a laser altimeter using the RZPN code modulation technique but also analyzing its ranging performance. [ABSTRACT FROM AUTHOR]

As a crucial part of ubiquitous networking and computing (UNC) technologies, low earth orbit (LEO) satellite communications aim at providing internet connectivity services everywhere. To improve the spectrum efficiency of satellite-to-ground communications, adaptive modulation and coding (AMC) are widely used, which can adjust the modulation and coding types according to the varying channel condition. However, satellite-to-ground communication channels have the characterizations such as fast dynamic change, fast switching, and significant fading. These characterizations make it challenging to predict the channel state information accurately and, thus, to perform accurate AMC. For example, rain loss is one of the crucial factors in satellite-to-ground channel fading. In general, it is difficult to build an integrated global model for rain loss because it varies in different regions around the world. Moreover, for the emerging applications of multiple antennas on satellites, the conventional look-up table method cannot cope with the high-dimensional inputs of the multiple antennas. To tackle the above challenges, we propose an AMC method based on deep learning (DL) and deep reinforcement learning (DRL) for ubiquitous satellite-to-ground networks. The proposed method directly processes real-time global weather and location information in the environment and intelligently selects encoding schemes to maximize system throughput. Simulation results show that the proposed method can increase the total throughput. The total number of correctly transmitted bits per unit time is improved, and the efficiency of the satellite-to-ground communication is enhanced. [ABSTRACT FROM AUTHOR]

The emerging 5G mobile networks are essential enablers for mobile virtual reality (VR) video streaming applications assuring high quality of experience (QoE) at the end-user. In addition, mobile edge computing brings computational resources closer to the user equipment (UE), which allows offloading computationally intensive processing. In this paper, we consider a network architecture for mobile VR video streaming applications consisting of a server that holds the VR video content, a mobile edge virtualization with prefetching (MVP) unit that handles the VR video packets, and a head-mounted display along with a buffer, which together serve as the UE. Several modulation and coding schemes with different rates are provided by the MVP unit to adaptively cope with the varying wireless link conditions to the UE and the state of the UE buffer. The UE buffer caches VR video packets as needed to compensate for the adaptive rates. A performance analysis is conducted in terms of blocking probability, throughput, queueing delay, and average packet error rate. To capture the effect of fading severity, the analytical expressions for these performance metrics are derived for Nakagami-m fading on the wireless link from the MVP unit to the UE. Numerical results show that the proposed system meets the network requirements needed to assure the QoE levels of different mobile VR video streaming applications. [ABSTRACT FROM AUTHOR]

In several wireless communication systems, robustness against jammers and covertness against eavesdroppers are required simultaneously. In this paper, we propose a novel covert anti-jamming communication system. The properties of both anti-jamming and covertness are achieved through the Gaussian-coded time-frequency modulation scheme. We propose two receiver algorithms based on the sparse signal recovery framework. The receiver algorithms estimate and remove the jamming signal from the received signal. In addition, it is difficult to distinguish the proposed signal from the actual Gaussian noise in both the time and frequency domains. We compare the covertness of the proposed communication system with that of a conventional digital modulation system in terms of the probability of detection. We numerically evaluated the bit error rate of the proposed system to demonstrate its anti-jamming performance. [ABSTRACT FROM AUTHOR]

In order to improve system coverage performance, in this paper, a multi-service transmission scheme on the basis of the puncturing technique, namely layered division multiplexing extension frequency-division multiplexing (LDM-Ex-FDM), is proposed. The key idea of the proposed scheme is that the symbols punctured from the enhanced layer (EL) of fixed services will be independently transmitted on a certain number of subcarriers orthogonal to the LDM signal of the core layer (CL) and most of the EL. By doing so, the punctured symbols will be demodulated with a higher signal-to-noise ratio (SNR) on the receiver side and can be recovered well, thus improving the reception performance of the EL fixed services. Moreover, two puncturing strategies based on bit-interleaved coded modulation (BICM) symbols of the LDM-Ex-FDM scheme, namely equal interval symbol puncturing (EISP) and non-equal interval symbol puncturing (NEISP), are developed to improve the performance of the EL services. Simulation results are given to show that, when the puncturing rate in the LDM-Ex-FDM scheme is configured as 1/12, the performance of the fixed service can be improved by 1.8 dB, meanwhile the bit error rate (BER) performance of the mobile service is not affected. Thus, the overall system coverage performance can be improved. Furthermore, to reduce the computational complexity and the demodulation delay of fixed service carried in the EL, at the receiver, a direct interference cancellation (DIC) detector is proposed as well. Simulation results are given to show that, under high injection level and high modulation order, the proposed DIC scheme is able to achieve almost the same BER performance as that of the traditional successive interference cancellation (SIC) scheme while with lower computational complexity. [ABSTRACT FROM AUTHOR]

A non-uniform constellation (NUC) can effectively reduce the gap between bit-interleaved coded modulation (BICM) capacity and Shannon capacity, which has been utilized in recent wireless broadcasting systems. However, the soft demapping algorithm needs a lot of Euclidean distance (ED) calculations and comparisons, which brings great demapping complexity to NUC. A universal low-complexity NUC demapping algorithm is proposed in this paper, which creates subsets based on the quadrant of the two-dimensional NUC (2D-NUC) received symbol or the sign of the in-phase (I)/quadrature (Q) component of the one-dimensional NUC (1D-NUC) received symbol. ED calculations and comparisons are only carried out on the constellation points contained in subsets. To further reduce the number of constellation points contained in subsets, the proposed algorithm takes advantage of the condensation property of NUC and regards a constellation cluster containing several constellation points as a virtual point. Analysis and simulation results show that, compared with the Max-Log-MAP algorithm, the proposed algorithm can greatly reduce the demapping complexity of NUC with negligible performance loss. [ABSTRACT FROM AUTHOR]

A bit-patterned media recording (BPMR) system is a type of ultrahigh-capacity magnetic storage system that can extend to an areal density of 1 terabit per square inch or higher. However, because the space between islands in the down- and cross-track directions is reduced to extend the areal density, the effect of two-dimensional interference is increased. However, using a staggered array, which is one of the possible island distributions for BPMR, helps to decrease intertrack interference. A 7/10 modulation code for a staggered BPMR is proposed to avoid the effect of two-dimensional interference and provide distance among nonidentical codewords for improving the correcting capability. [ABSTRACT FROM AUTHOR]

Featured Application: The method described can be used to assess whether the signal received in the underwater acoustic communication system can be modelled as a stochastic wide-sense stationary process. The fulfillment of this condition is necessary both to calculate the basic transmission parameters of the communication channel, such as coherence bandwidth and coherence time, and to correctly detect information transmitted in a UAC systems using modern modulation and coding schemes, such as orthogonal frequency-division multiplexing or spread spectrum techniques. A fast and energy efficient method of assessing whether the received signal meets the WSS assumption can be implemented in a UAC adaptive system, enabling the change of modulation parameters, in particular, the duration of the modulation symbol for which the WSS assumption is fulfilled, thereby increasing the UAC system's reliability. The performances of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Designing the physical layer of a reliable data transmission system requires a knowledge of channel characteristics in terms of the specific parameters of the stochastic model. The Wide-Sense Stationary Uncorrelated Scattering (WSSUS) assumption simplifies the stochastic description of the channel, and thus the estimation of its transmission parameters. However, shallow underwater channels may not meet the WSSUS assumption. This paper proposes a method for testing the Wide-Sense Stationary (WSS) part of the WSSUS feature of a UAC channel on the basis of the complex envelope of a received probe Pseudo-Random Binary Sequence (PRBS) signal. Two correlation coefficients are calculated that can be interpreted, together, as a measure that determines whether the channel is WSS or not. A similar wide-sense stationarity assessment can be performed on the basis of the Time-Varying Impulse Response (TVIR) of a UAC channel. However, the method proposed in this paper requires fewer computational operations in the receiver of a UAC system. PRBS signal transmission tests were conducted in the UAC channel simulator and in real conditions during an inland water experiment. The correlation coefficient values obtained using the method based on the envelope of a probe signal and the method of analysing the TVIR estimates are compared. The results are similar, and thus, it is possible to assess if the UAC channel can be modelled as a WSS stochastic process without the need for TVIR estimation. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is the technique proposed for multiple access in the fifth generation (5G) cellular network. In NOMA, different users are allocated different power levels and are served using the same time/frequency resource blocks (RBs). The main challenges in existing NOMA systems are the limited channel feedback and the difficulty of merging it with advanced adaptive coding and modulation schemes. Unlike formerly proposed solutions, in this paper, we propose an effective channel estimation (CE) algorithm based on the long-short term memory (LSTM) neural network. The LSTM has the advantage of adapting dynamically to the behavior of the fluctuating channel state. On average, the use of LSTM results in a 10% lower outage probability and a 37% increase in the user sum rate as well as a maximal reduction in the bit error rate (BER) of 50% in comparison to the conventional NOMA system. Furthermore, we propose a novel power coefficient allocation algorithm based on binomial distribution and Pascal's triangle. This algorithm is used to divide power among N users according to each user's channel condition. In addition, we introduce adaptive code rates and rotated constellations with cyclic Q-delay in the quadri-phase shift keying (QPSK) and quadrature amplitude modulation (QAM) modulators. This modified modulation scheme overcomes channel fading effects and helps to restore the transmitted sequences with fewer errors. In addition to the initial LSTM stage, the added adaptive coding and modulation stages result in a 73% improvement in the BER in comparison to the conventional NOMA system. [ABSTRACT FROM AUTHOR]