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This letter presents two results for multiuser wireless systems employing dirty-paper coding strategies along with greedy scheduling over the broadcast multiple-input multiple-output channel. Specifically, an efficient and suboptimal downlink scheduler is proposed to approximate the maximum sum rate using equal power allocation, and it is shown to approach the maximum sum rate of optimal power allocation for a large number of users under optimal scheduling. The second result demonstrates that the average maximum sum rate can be tightly upper bounded when spatial multiplexing is maximized. [ABSTRACT FROM AUTHOR]

This paper investigates intelligent reflecting surface based backscatter communication (IRS-BackCom), in order to realize computational task offloading of energy-constrained mobile edge computing network in a self-sustainable manner. Specifically, the system operation is divided into two phases. In the first one, the ambient signal energy from a power beacon (PB) either provides the energy supply of local computing and energy harvesting circuits, or flows into the energy storage, when reaching the IRS. In the second one, the stored energy is used to enable IRS-BackCom for partial computational data offloading and energize local computing circuit. Based on this, the maximization problem of sum computational bits is formulated. By jointly optimizing the beamforming vector at the PB, the backscatter matrix at the IRS, the time scheduling of two-phase process, as well as the time of local computing, sum computational bits are maximized. In addition, this paper proposes element clustering to realize BackCom, so as to reduce the control and computation complexity of IRS. According to different operating mechanisms, two cluster operation modes are considered, namely independent cluster operation mode and joint cluster operation mode. Simulation results demonstrate the achievable sum computational bits by the proposed IRS-BackCom schemes. [ABSTRACT FROM AUTHOR]

This paper studies a multiple-input–single-output (MISO) broadcast channel (BC) featuring simultaneous wireless information and power transfer, where a multiantenna access point (AP) delivers both information and energy via radio signals to multiple single-antenna receivers simultaneously, and each receiver implements either information decoding (ID) or energy harvesting (EH). In particular, pseudorandom sequences that are a priori known and therefore can be cancelled at each ID receiver are used as the energy signals, and the information-theoretically optimal dirty paper coding is employed for the information transmission. We characterize the capacity region for ID receivers by solving a sequence of weighted sum-rate (WSR) maximization (WSRMax) problems subject to a maximum sum-power constraint for the AP, and a set of minimum harvested power constraints for individual EH receivers. The problem corresponds to a new form of WSRMax problem in MISO-BC with combined maximum and minimum linear transmit covariance constraints (MaxLTCCs and MinLTCCs), which differs from the celebrated capacity region characterization problem for MISO-BC under a set of MaxLTCCs only and is challenging to solve. By extending the general BC–multiple-access-channel duality, which is only applicable to WSRMax problems with MaxLTCCs, and applying the ellipsoid method, we propose an efficient iterative algorithm to solve this problem globally optimally. Furthermore, we also propose two suboptimal algorithms with lower complexity by assuming that the information and energy signals are designed separately. Finally, numerical results are provided to validate our proposed algorithms. [ABSTRACT FROM PUBLISHER]

The cell-free massive multiple-input multiple-output (CFmMIMO) aims to provide uniform quality of service (QoS) for all users, and can be used in small-area scenarios such as indoor industrial networks. This paper studies the CFmMIMO system for indoor industrial scenarios. Firstly, an access point (AP) grouping based hierarchical network topology is proposed. Based on this, we propose an effective AP selection method. To reduce pilot contamination, a pilot assignment scheme based on inspection robot (IR) location is proposed. Considering the high reliability requirement of industrial data transmission, the power control and backhaul combining are jointly optimized to maximize the minimum signal to interference plus noise ratio (SINR). The scalability of the proposed CFmMIMO system is analyzed, and a scalable power control method is proposed. The simulations demonstrate the effectiveness of the AP selection method, pilot assignment scheme, and the joint optimization algorithm for power control and backhaul combining. Moreover, the impact of network scale and network load on system performance is evaluated and analyzed in the simulations. [ABSTRACT FROM AUTHOR]

Coded caching is an emerging technique to reduce the data transmission load during the peak-traffic times. In such a scheme, each file in the data center or library is divided into a number of packets to pursue a low broadcasting rate based on the designed placements at each user’s cache. However, the implementation complexity of this scheme increases with the number of packets. It is crucial to design a scheme with a small subpacketization level, while maintaining a relatively low transmission rate. Recently, a combinatorial structure called placement delivery array (PDA) was proposed as an effective tool to design coded caching schemes with a relatively low subpacketization level. This paper proposes a novel PDA construction by selecting proper orthogonal arrays (POAs), which generalizes the existing construction but with a more flexible memory size. Based on the proposed PDA construction, an effective transform is further proposed to enable a coded caching scheme to achieve a smaller subpacketization level. Moreover, two new coded caching schemes with the coded placement are derived. It is shown that the proposed schemes can yield a lower subpacketization level or transmission rate over the benchmark schemes. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel optimization model for multiple Unmanned Aerial Vehicles (UAVs) working simultaneously as relays to help two set of ground users; namely relay users and device-to-device (D2D) users. The relay users are assumed out communication rages from each other and use the UAV link to for their data transmission. While the D2D users are assumed to be nearby users and use the UAV for managing the resources without being involved in the transmission. The goal of the paper is to operate the UAVs in an energy-efficient manner to support the different set of users by i) optimizing the available bandwidth and power allocations of the D2D links, and ii) acting as relays when needed to maintain the communication links between relay users. We formulate an optimization problem that maximizes the throughput-energy utility while respecting the resource availability including the UAVs’ energy consumption, UAV-user association, and trajectory constraints. Due to the non-convexity of the problem, we propose to solve it in three steps using Taylor series approximation. Firstly, we optimize the transmit power of the UAVs and users. Then, we optimize the bandwidth allocation for a given transmit power values. Finally, an efficient heuristic algorithm based on a recursive shrink-and-realign process is proposed to optimize the UAVs’ trajectories. The performance of the proposed method shows advantages in terms of average throughput compared to the fixed power and bandwidth solutions. [ABSTRACT FROM AUTHOR]

A memoryless bivariate Gaussian source is transmitted to a pair of receivers over an average-power limited bandwidth-matched Gaussian broadcast channel. Based on their observations, Receiver 1 reconstructs the first source component while Receiver 2 reconstructs the second source component both seeking to minimize the expected squared-error distortions. In addition to the source transmission digital information at a specified rate should be conveyed reliably to Receiver 1–the “stronger” receiver. Given the message rate we characterize the achievable distortions region. Specifically, there is an ${\sf SNR}$ -threshold below which Dirty Paper coding of the digital information against a linear combination of the source components is optimal. The threshold is a function of the digital information rate, the source correlation and the distortion at the “stronger” receiver. Above this threshold a Dirty Paper coding extension of the Tian-Diggavi-Shamai hybrid scheme is shown to be optimal. [ABSTRACT FROM AUTHOR]

The differential chaos shift keying with code index modulation (CIM-DCSK) using Walsh codes can increase the data rate, but error rate performance degrades over practical multipath channel with high delay spread. To tackle this drawback, this paper proposes a parallel CIM-DCSK (PT-CIM-DCSK), where the first time slot is used to transmit the chaotic reference sequence, and the second slot is used to transmit the multiple sequences carrying data bits. In particular, multiple $q$ chaotic sequences are added for data transmission in parallel, and each sequence is modulated by CIM-DCSK with $m_{c}$ bits. By exploiting the quasi-orthogonal characteristics of permuted chaotic signals, the interference between $q$ sequences can be remarkably suppressed. In this way, given the data rate, PT-CIM-DCSK can achieve a larger length of Walsh segment than the CIM-DCSK, since its parallel transmission compensates the rate. In addition, the error performance of the proposed scheme over the multipath Rayleigh fading channel is theoretically analyzed. The theoretical and consistent simulation results demonstrate that the PT-CIM-DCSK can obtain significant performance gains over the conventional CIM-DCSK, and the gain can be up to 5 dB in multipath fading channel with high delay. This is because the larger Walsh segment of PT-CIM-DCSK provides the enhanced robustness against multipath effect. The performance superiority of the proposed scheme is further verified in practical ultra-wideband (UWB) wireless industrial scenarios, which suggests promising for low-cost and low-complexity wireless communication applications. [ABSTRACT FROM AUTHOR]

In this paper, the performance of a wireless system, which is beneficial from utilization of multiple reconfigurable intelligent surfaces (RISs) and the direct link between the source node and the mobile user, is analyzed. Especially, the effect of transceiver hardware impairments (HIs) are taken into consideration. We successfully derive the outage probability (OP), throughput, achievable data rate (ADR), and symbol error probability (SEP) expressions of this multiple-RIS assisted wireless systems with and without HIs (referred as RIS-HI and RIS-ID system, respectively) over Nakagami- $m$ fading channels. The above performance factors are also benchmarked with the case that only a point-to-point (P2P) link without RIS is considered (denotes as as P2P-HI and P2P-ID systems for HI and ideal hardware conditions, respectively). All obtained formulas are verified by Monte-Carlo simulations. It is observed that the RIS-HI system significantly outperforms the P2P-HI system at low transmit power regime, while the performance of the RIS-ID system is always better than that of P2P-ID system. On the other hand, HIs show more severe effect for higher data transmission rates or high modulation orders. [ABSTRACT FROM AUTHOR]

In millimeter-wave (MMW) multiple-input multiple-output (MIMO) communications, users and their corresponding base station (BS) have to align their beam during both initial access and data transmissions to compensate for the high propagation loss. The beam alignment (BA) procedure specified for 5th Generation (5G) New Radio (NR) has been designed to be fast and precise in the presence of non-malicious interference and noise. A smart jammer might exploit this weakness and may launch an attack during the BA phase in order to degrade the accuracy of beam selection and, thus, adversely impacting the end-to-end performance and quality-of-service experienced by the users. In this paper, we study the effects of a jamming attack at MMW frequencies during the BA procedure used to perform initial access for idle users and adaptation/recovery for connected users. We show that the BA procedure adopted in 5G NR is extremely vulnerable to a smart jamming attack and, consequently, we propose a countermeasure based on the idea of randomized probing, which consists of randomly corrupting the probing sequence transmitted by the BS in order to reject the jamming signal at the UE via a subspace-based technique based on orthogonal projections and jamming cancellation. Numerical results corroborate our theoretical findings and show the very satisfactory accuracy of the proposed anti-jamming approach. [ABSTRACT FROM AUTHOR]

Due to the considerable fading arising from the long-distance transmission between satellites and terrestrial terminals as well as the complex geographic environments on the earth, aerial relays have been designed to facilitate the information delivery between the satellites and terrestrial terminals when reliable direct data transmissions cannot be achieved. In this paper, a cooperative satellite-aerial-terrestrial network (CSATN) system including a satellite (S), an aerial relay (R), and a terrestrial receiver (D) is considered, while decode-and-forward relay scheme is adopted. Specifically, inspired by the beam shape of the transmission signal from S, we model the operation space of R as a circular truncated cone to accurately reflect the practical large-scale transmission scenarios, the height of which is decided by the upper and lower limitations of the operation height of R. Thus, considering the randomness of R and D and employing geometric probability theory, the exact and asymptotic outage probability (OP) of S-R, S-D, and R-D links is studied, and then the end-to-end outage performance of CSATN is investigated accordingly by using approximation method. Finally, numerical results are presented to validate our proposed analysis. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) has emerged as a promising technique to enhance wireless communication performance cost-effectively. The existing literature has mainly considered IRS being deployed near user terminals to improve their performance. However, this approach may incur a high cost if IRSs need to be densely deployed in the network to cater to random user locations. To avoid such high deployment cost, in this paper we consider a new IRS aided wireless network architecture, where IRSs are deployed in the vicinity of each base station (BS) to assist in its communications with distributed users regardless of their locations. Besides significantly enhancing IRSs’ signal coverage, this scheme helps reduce the IRS-associated channel estimation overhead as compared to conventional user-side IRSs, by exploiting the nearly static BS-IRS channels over short distance. For this scheme, we propose a new two-stage transmission protocol to achieve IRS channel estimation and reflection optimization for uplink data transmission efficiently. In addition, we propose effective methods for solving the user-IRS association problem based on long-term/statistical channel knowledge and the selected user-IRS-BS cascaded channel estimation problem. Finally, all IRSs’ passive reflections are jointly optimized with the BS’s multi-antenna receive combining to maximize the minimum achievable rate among all users for data transmission. Numerical results show that the proposed co-site-IRS empowered BS scheme can achieve significant performance gains over the conventional BS without co-site IRS and existing schemes for IRS channel estimation and reflection optimization, thus enabling an appealing low-cost and high-performance BS design for future wireless networks. [ABSTRACT FROM AUTHOR]

Online fountain codes (OFCs) have many advantages, such as low overhead, online feedback and optimal encoding, due to the feedback of the instantaneous decoding state. This paper analyzes the characteristics of underwater acoustic networks (UANs) as well as the issues of existing OFCs applied in UANs. Aiming at these issues, two optimization objectives of OFCs are put forward for UANs. In addition, a recursive OFC with limited feedback (ROFC-LF) is presented for UANs. The ROFC-LF reduces the consumption of bandwidth and energy caused by the transmission of useless coding packets. Through limited feedback, the problem of low channel utilization in UANs with half-duplex communication is solved. Furthermore, a data transmission mechanism based on the ROFC-LF for UANs is presented. The theoretical analysis and simulation results show that the proposed transmission mechanism based on the ROFC-LF scheme outperforms the existing OFC schemes in terms of overhead, computational complexity, coding efficiency and energy consumption. Consequently, the ROFC-LF is suitable for UANs with constrained resources. [ABSTRACT FROM AUTHOR]

In this paper, we propose a precoded faster-than-Nyquist (FTN) signaling technique for time-domain single-carrier index-modulated symbol transmission. More precisely, eigenvalue decomposition (EVD) precoding is adopted for the FTN transmission of data bits modulated by single-carrier time-domain index modulation (IM). While the FTN scheme increases the spectral efficiency and data rate by increasing the density of transmit symbols, the time-domain IM works towards the same objective while maintaining symbol sparsity. We analytically derive the constrained capacity of the proposed system. Our simulation results show that the proposed scheme has better bit error ratio (BER) performance than the conventional FTN-IM scheme, particularly for the scenario of a higher packing ratio. With the proposed scheme, a 2.5 dB performance gain is observed at the BER of 10−4, where the packing ratio is 0.7 and the roll-off factor is 0.5 in the channel-uncoded scenario. We further analyze our scheme’s performance by characterizing its minimum Euclidean distance and inter-symbol interference. Furthermore, we present a three-stage serially concatenated iterative detection architecture for the proposed EVD-FTN-IM signaling scheme. It is demonstrated in our simulations that a near-capacity BER performance is achievable in the proposed turbo-coded FTN-IM scheme. [ABSTRACT FROM AUTHOR]

To realize high energy-efficient, high spectrum-efficient, and high-throughput data transmission, a multi-carrier differential chaos shift keying communication system with hybrid index modulation, referred to as HIM-MC-DCSK system, is proposed in this paper. In the HIM-MC-DCSK system, we intelligently integrate the carrier-number-index technique and carrier-index technique into the MC-DCSK modulation in order to significantly boost the transmission efficiency in wireless communication systems. Especially, we use a pair of orthogonal signals to represent the active and inactive subcarriers in the HIM-MC-DCSK system so as to exploit all the subcarriers to transmit information bits. In addition, the theoretical bit-error-rate (BER) expressions of the HIM-MC-DCSK system are derived over additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels. Also, the data rate, spectrum efficiency, energy efficiency, and complexity of the proposed system are carefully analyzed. Monte-Carlo simulations not only verify the accuracy of the theoretical analysis but also illustrate the superiority of the proposed system. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) and massive MIMO systems are intrinsic components of 5G and beyond. These systems rely on using beamforming codebooks for both initial access and data transmission. Current beam codebooks, however, generally consist of a large number of narrow beams that scan all possible directions, leading to large training overhead. Further, these codebooks do not normally account for hardware impairments or possible non-uniform array geometries, and their calibration process is expensive. To overcome these limitations, this paper develops an efficient online machine learning framework that learns how to adapt the codebook beam patterns to the specific deployment, surrounding environment, user distribution, and hardware characteristics. This is done by designing a novel complex-valued neural network architecture in which the neuron weights directly model the beamforming weights of the analog phase shifters, accounting for the key hardware constraints. This model learns the codebook beams through online and self-supervised training avoiding the need for explicit channel state information. This respects the practical situations where the channel is imperfect or hard to obtain. Simulation results highlight the capability of the proposed solution in learning environment and hardware aware beam codebooks, which reduce the training overhead and improve the robustness against possible hardware impairments. [ABSTRACT FROM AUTHOR]

The incorporation of intelligent reflecting surface (IRS) into wireless communication systems can extend the coverage and enhance the data transmission rate. This paper studies the joint transceiver and IRS designs in IRS-assisted multi-input multi-output (MIMO) systems under both perfect channel state information (CSI) and imperfect CSI. Specifically, the transmit precoder, reflection coefficients at the IRS, and receive equalizer are jointly optimized to minimize the data detection mean square error (MSE), subject to the transmission power constraint and the modulus constraints for IRS reflection coefficients. The design problems, non-convex and challenging, are tackled under the framework of alternating optimization. For the design with perfect CSI, we successively optimize the IRS reflection coefficients given the precoder and present the closed-form optimal angle of one reflection coefficient given the others. For the robust design with imperfect CSI, we first average the detection MSE over channel uncertainties by using a generalized statistical CSI error model. Then, the averaged MSE is approximated by a more tractable upper bound. Subsequently, the robust design problem is elaborately transformed into a form similar to the problem with perfect CSI. Numerical results demonstrate the effectiveness of the proposed designs as compared to various benchmark schemes. [ABSTRACT FROM AUTHOR]

One of the most promising technologies to be employed in beyond 5G networks is based on the concept of cell-free (CF) massive MIMO, in which a predetermined set of access points (APs) jointly cooperate in the data transmission and reception to/from the user equipment (UE). In order to efficiently manage radio resources, the CF central processing unit implement uplink power control policies. These policies aim to optimize a given network utility function. In this paper, we investigate the max-min fairness optimization problem, in which the spectral efficiency performance of the UE with the worst channel conditions is prioritized, taking into account a per-UE power constraint and assuming linear maximum ratio combining at APs. Existing solutions have typically relied on second-order cone programming with convex approximations, which exhibit high computational complexity and scalability issues. Therefore, meta-heuristics (MHs) are explored as alternative optimization schemes, capable of providing (near)-optimal solutions with reasonable computational effort. Three MH approaches with different operation principles are compared. Numerical results show that the differential evolution algorithm exhibits the best trade-off between solution quality and run time, being able to reach (near)-optimal solutions faster than the bisection approach while coping with the scalability issues of the geometric programming-based algorithm. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) and terahertz MIMO systems rely on pre-defined beamforming codebooks for both initial access and data transmission. These pre-defined codebooks, however, are commonly not optimized for specific environments, user distributions, and/or possible hardware impairments. This leads to large codebook sizes with high beam training overhead which makes it hard for these systems to support highly mobile applications. To overcome these limitations, this paper develops a deep reinforcement learning framework that learns how to optimize the codebook beam patterns relying only on the receive power measurements. The developed model learns how to adapt the beam patterns based on the surrounding environment, user distribution, hardware impairments, and array geometry. Further, this approach does not require any knowledge about the channel, RF hardware, or user positions. To reduce the learning time, the proposed model designs a novel Wolpertinger-variant architecture that is capable of efficiently searching the large discrete action space. The proposed learning framework respects the RF hardware constraints such as the constant-modulus and quantized phase shifter constraints. Simulation results confirm the ability of the developed framework to learn near-optimal beam patterns for line-of-sight (LOS), non-LOS (NLOS), mixed LOS/NLOS scenarios and for arrays with hardware impairments without requiring any channel knowledge. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) builds upon the dual use of LED-based lighting infrastructure for data transmission. It is particularly attractive for user-dense environments and mainly positioned as a complementary wireless access technology to radio-frequency (RF) counterparts. The practical implementation of hybrid light/radio access networks requires the design of efficient vertical and horizontal handover mechanisms to exploit their complementary features. In this paper, we propose an event-triggered adaptive handover mechanism for centralized hybrid VLC/millimeter wave (MMW) systems. Unlike distributed architectures where all the functionalities are deployed in each access point (AP), the centralized systems allow better optimization of network parameters due to awareness of global network view. The proposed handover mechanism takes advantage of this architecture and uses offset-enhanced signal-to-interference plus noise ratio levels of APs as performance metrics. To ensure balanced distribution of user equipment (UE) numbers between two underlying technologies, it auto-tunes the offset variables using rule-set based algorithms based on the number of connected UEs and data rates as inputs. Our results demonstrate that the proposed handover mechanism significantly improves hybrid system performance via adaptive tuning of AP selection parameter while minimizing signaling overhead. [ABSTRACT FROM AUTHOR]

We consider a single-hop wireless sensor network in which each sensor node has an individual elastic data stream to transmit to each other node. We refer to this traffic pattern as unicast in this paper. The network has multiple slotted channels available for the data transmissions. To guarantee successful unicast within a bounded delay, we consider deterministic schemes that pre-assign each node a periodic schedule sequence to schedule transmitting and receiving at each time slot. The sequence period should be minimized since it upper bounds the unicast delay. We have investigated both synchronous TDMA sequences and asynchronous sequences. Since accurate time synchronization is difficult to achieve in sensor networks, we mainly present analysis and design for asynchronous sequences. In this paper, for a group-based channel assignment, we present a lower bound on the common period and propose a sequence construction method by which the period can achieve the same order as the lower bound. We also analyze optimal transmitting and receiving probabilities for two random schemes and compare their frequency utilization efficiency. Finally, unicast delay and energy consumption performance are compared by simulations. [ABSTRACT FROM AUTHOR]

Existing optical and wireless networks designed to support today’s services may not be suitable for the emerging services, such as machine-to-machine applications of the Internet-of-Things paradigm and tactile-haptic applications of the Tactile Internet paradigm. Some of these applications must adhere to stringent quality of service requirements, especially an ultra-low end-to-end latency constraint of approximately 1 ms. In this paper, we investigate the feasibility of the wireless local area network (WLAN) infrastructure, specifically the IEEE 802.11 HCF Controlled Channel Access (HCCA) media access control (MAC) protocol, in supporting low-latency applications. The scenario considered is tactile-haptic data transmission between body-worn data collection devices and a wireless access point. In particular, we focus on uplink direction rather than downlink direction, because uplink data transmission forms a latency bottleneck of this particular network. In this paper, we first formulate an analytical model of the HCCA using a queuing theory to evaluate the average uplink latency. We then carry out global sensitivity analyses to understand the implications of various timing and network parameters on the uplink latency. Using these insights, we propose a novel strategic parameter selection (SPS) algorithm that effectively reduces uplink latency of the IEEE 802.11 WLAN. This paper provides insights into WLAN design such that latency-sensitive applications can be supported in the near future. [ABSTRACT FROM AUTHOR]

This paper analyzes the multiplexing gains (MG) for simultaneous transmission of delay-sensitive and delay-tolerant data over interference networks. In the considered model, only delay-tolerant data can profit from coordinated multipoint (CoMP) transmission or reception techniques, because delay-sensitive data has to be transmitted without further delay. Transmission of delay-tolerant data is also subject to a delay constraint, which is however less stringent than the one on delay-sensitive data. Different coding schemes are proposed, and the corresponding MG pairs for delay-sensitive and delay-tolerant data characterized for Wyner’s linear symmetric network and for Wyner’s two-dimensional hexagonal network with and without sectorization. Information-theoretic converses are established for these models. For Wyner’s linear symmetric network the bounds match whenever the cooperation rates are sufficiently large or the delay-sensitive MG is small or moderate. These results show that on Wyner’s symmetric linear network and for sufficiently large cooperation rates, the largest MG for delay-sensitive data can be achieved without penalizing the maximum sum-MG of both delay-sensitive and delay-tolerant data. Our achievable schemes show that a similar conclusion holds for Wyner’s hexagonal network only for the model with sectorization. In the model without sectorization, a penalty in sum-MG is incurred whenever one insists on a positive delay-sensitive MG [ABSTRACT FROM AUTHOR]

The performance of grant-free random access (GF-RA) is limited by the number of accessible random access resources (RRs) due to the absence of collision resolution. Compressive sensing (CS)-based RA schemes scale up the RRs at the expense of increased non-orthogonality among transmitted signals. This paper presents the design of multi-sequence spreading random access (MSRA) which employs multiple spreading sequences to spread the different symbols of a user as opposed to the conventional schemes in which a user employs the same spreading sequence for each symbol. We show that MSRA provides code diversity, enabling the multi-user detection (MUD) to be modeled into a well-conditioned multiple measurement vectors (MMVs) CS problem. The code diversity is quantified by the decrease in the average Babel mutual coherence among the spreading sequences. Moreover, we present a two-stage active user detection (AUD) scheme for both wideband and narrowband implementations. Our theoretical analysis shows that with MSRA activity misdetection falls exponentially while the size of GF-RA frame is increased. Finally, the simulation results show that about 82% increase in utilization of RRs, i.e., more active users, is supported by MSRA than the conventional schemes while achieving the RA failure rate lower bound set by random access collision. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of a full-duplex (FD) relay system where multi-antennas are exploited at source and destination. Unlike previous works, the impacts of imperfect channel state information (I-CSI), transceiver hardware noise (THN), and residual self-interference (RSI) are taken into account. We mathematically derive the exact closed-form expressions of the outage probability (OP), symbol error rate (SER), and ergodic capacity (EC) of the FD relay system with I-CSI, THN, and RSI over Nakagami- $m$ fading channels. From the derived expressions, the performance of the considered system under the effects of three negative factors (I-CSI, THN, and RSI) is compared with that system in the case of all ideal factors (perfect channel state information (P-CSI), perfect transceiver hardware (P-TH) and perfect self-interference cancellation (P-SIC)), two ideal factors (P-CSI and P-TH, P-CSI and P-SIC, P-TH and P-SIC), or one ideal factor (P-CSI or P-TH or P-SIC). Numerical results show a strong impact of three negative factors on the OP, SER, and EC of the considered FD relay system, especially when the data transmission rate of the system and signal-to-noise ratio (SNR) are high. In particular, OP, SER, and EC go to the floors in the high SNR regime due to the three negative factors. Therefore, when I-CSI, THNs, and RSI exist in the FD relay system, we should use suitable source and relay transmission power to obtain excellent performance while saving energy consumption. Moreover, when two of the three negative factors are large enough, the remaining factor’s impact becomes weaker and may be neglected in certain circumstances. [ABSTRACT FROM AUTHOR]

In this paper, we devise a highly efficient machine learning-based channel estimation for orthogonal frequency division multiplexing (OFDM) systems, in which the training of the estimator is performed online. A simple learning module is employed for the proposed learning-based estimator. The training process is thus much faster and the required training data is reduced significantly. Besides, a training data construction approach utilizing least square (LS) estimation results is proposed so that the training data can be collected during the data transmission. The feasibility of this novel construction approach is verified by theoretical analysis and simulations. Based on this construction approach, two alternative training data generation schemes are proposed. One scheme transmits additional block pilot symbols to create training data, while the other scheme adopts a decision-directed method and does not require extra pilot overhead. Simulation results show the robustness of the proposed channel estimation method. Furthermore, the proposed method shows better adaptation to practical imperfections compared with the conventional minimum mean-square error (MMSE) channel estimation. It outperforms the existing machine learning-based channel estimation techniques under varying channel conditions. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmwave) communications, envisaged for the next generation wireless networks, rely on large antenna arrays and very narrow, high-gain beams. This poses significant challenges to beam alignment between transmitter and receiver, which has attracted considerable research attention. Even when alignment is achieved, the link is subject to beam drift (BD). BD, caused by non-ideal features inherent in practical beams and rapidly changing environments, is referred to as the phenomenon that the center of main-lobe of the used beam deviates from the real dominant channel direction, which further deteriorates the system’s performance. To mitigate the BD effect, in this paper we first theoretically analyze the BD effect on the performance of outage probability as well as effective achievable rate, which takes practical factors (e.g., the rate of change of the environment, beam width, transmit power) into account. Then, different from conventional practice, we propose a novel design philosophy where multi-resolution beams with varying beam widths are used for data transmission while narrow beams are employed for beam training. Finally, we design an efficient learning based algorithm which can adaptively choose an appropriate beam width according to the environment. Simulation results demonstrate the effectiveness and superiority of our proposals. [ABSTRACT FROM AUTHOR]

A novel approach is here presented to superimpose a low-priority data stream on a high-priority data stream for OFDM systems. The main improvement with respect to conventional hierarchical modulation, which is included with the same purpose in various wireless technologies, is that the low-priority data stream can be decoded from the received subcarrier symbols without any previous equalization for multipath fading channels. As a consequence, the expected performance is nearly invariant of the channel estimation method used to equalize the channel. The low-priority stream is inserted adopting a gain-invariant dirty paper coding based on Rational Dither Modulation, which was proposed for data hiding applications. In this paper an analysis of the developed system is presented and several simulations have been carried out using DVB-T system parameters to verify the validity of the proposed approach. The experimental results show the better performance of the proposed method with respect to that of a conventional hierarchical modulation, particularly when the accuracy of the estimated channel response decreases. [ABSTRACT FROM PUBLISHER]

Frequency-hopping (FH) MIMO radar is recently introduced as an underlying system for realizing dual-function radar-communication (DFRC), increasing communication symbol rates to multiples of the radar pulse repetition frequency. As a newly conceived DFRC system, many realistic issues, such as channel estimation and synchronization, are not effectively solved yet. In this paper, we develop a multi-antenna receiver-based downlink communication scheme for the FH-MIMO DFRC, addressing the above issues in multi-path channels. By exploring the unique FH-MIMO radar waveform, we suppress both inter-antenna and inter-hop interference, and introduce minimal constraints on the radar waveform to facilitate DFRC. We then develop accurate estimation methods for timing offset and channel parameters. These methods are further employed to design reliable demodulation methods. We also derive performance bounds for the proposed estimation methods and embedded communications. Simulation results validate the efficacy of our receiving scheme, showing that the performance of estimators and data communications approaches analytical bounds. [ABSTRACT FROM AUTHOR]

Low-latency communication is expected to play a key role in the Industrial Internet of Things (IIoT). Although there has been considerable effort on reducing latency, few attention has been focused on the low-latency transmission of distortion-tolerant data, e.g. IIoT’s analog samples, over fading channels. In this paper, we present a cross-layer approach to jointly adapt the transmission power, rate, and compression ratio based on the instantaneous buffer and channel states. In particular, to minimize the average delay under both average power and distortion constraints, we formulate a Constrained Markov Decision Process (CMDP) with multi-dimensional state and action spaces. A novel solution is then presented by judiciously decomposing the multi-dimensional CMDP into a deterministic hierarchical optimization consisting of a linear programming and a convex optimization problem. Furthermore, we show the optimality of a threshold-based scheduling policy that highly reduces the complexity and present an optimal delay-power-distortion tradeoff that characterizes a fundamental performance tradeoff between the physical, network, and application layers. The joint lossy compression and power allocation scheme realizes a deep cross-layer optimization of source coding, queuing control, and wireless transmission, which outperforms the traditional cross-layer design consisting of only two layers, not to mention layered protocols. [ABSTRACT FROM AUTHOR]

Edge caching is an efficient technique for mitigating redundant data transmissions over backhaul links. Contents are constantly evolving, and thus the cached contents should be updated timely to guarantee freshness. Information freshness is captured by the Age of Information (AoI) metric. In this paper, we explore a content resale problem, where a Network Service Provider (NSP) purchases contents from Content Providers (CPs) then sells contents to users. We model the problem as a three-stage sequential problem. Then we decompose the problem into two sub-problems on deciding the contents to be purchased and cached, and the respective prices. We solve the sub-problems through the framework of Stackelberg game and auction respectively. For the content purchase, we consider four different cases to design the auction mechanisms. In the auctions, the NSP has to reveal its private information due to the AoI characteristics. Furthermore, we prove that such disclosure will not bring the loss of the NSP’s utility. Finally, numerical results in different cases are provided to show that the NSP can efficiently exploit the benefit from the knowledge about CPs’ production costs and the competition among CPs under our proposed mechanism. [ABSTRACT FROM AUTHOR]

This paper introduces a unified deep neural network (DNN)-based precoder for two-user multiple-input multiple-output (MIMO) networks with five objectives: data transmission, energy harvesting, simultaneous wireless information and power transfer, physical layer (PHY) security, and multicasting. First, a rotation-based precoder is developed to solve the above problems independently. Rotation-based precoding is a new precoding and power allocation scheme that beats existing solutions for PHY security and multicasting and is reliable in different antenna settings. Next, a DNN-based precoder is designed to unify the solution for all objectives. The proposed DNN concurrently learns the solutions given by conventional methods, i.e., analytical or rotation-based solutions. A binary vector is designed as an input feature to distinguish the objectives. Numerical results demonstrate that, compared to the conventional solutions, the proposed DNN-based precoder reduces on-the-fly computational complexity more than an order of magnitude while reaching near-optimal performance (99.45% of the averaged optimal solutions). The new precoder is also more robust to the variations of the numbers of antennas at the receivers. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is a promising new paradigm to achieve high spectral and energy efficiency for future wireless networks by reconfiguring the wireless signal propagation via passive reflection. To reap the promising gains of IRS, channel state information (CSI) is essential, whereas channel estimation errors are inevitable in practice due to limited channel training resources. In this paper, in order to optimize the performance of IRS-aided multiuser communications with imperfect CSI, we propose to jointly design the active transmit precoding at the access point (AP) and passive reflection coefficients of the IRS, each consisting of not only the conventional phase shift and also the newly exploited amplitude variation. First, the achievable rate of each user is derived assuming a practical IRS channel estimation method, which shows that the interference due to CSI errors is intricately related to the AP transmit precoders, the channel training power and the IRS reflection coefficients during both channel training and data transmission. Next, for the single-user case, by combining the benefits of the penalty method, Dinkelbach method and block successive upper-bound minimization (BSUM) method, a new penalized Dinkelbach-BSUM algorithm is proposed to optimize the IRS reflection coefficients for maximizing the achievable data transmission rate subjected to CSI errors; while for the multiuser case, a new penalty dual decomposition (PDD)-based algorithm is proposed to maximize the users’ weighted sum-rate. Finally, simulation results are presented to validate the effectiveness of our proposed algorithms as compared to benchmark schemes. In particular, useful insights are drawn to characterize the effect of IRS reflection amplitude control (with/without the conventional phase-shift control) on the system performance under imperfect CSI. [ABSTRACT FROM AUTHOR]

There is a growing interest in the transition from 4-step random access to 2-step random access in machine-type communication (MTC), since 2-step random access is well-suited to short message delivery in various Internet of Things (IoT) applications. In this paper, we study a 2-step random access approach that uses code division multiple access (CDMA) to form multiple channels for data packet transmissions with a spreading factor less than the number of channels. As a result, the length of data transmission phase in 2-step random access can be shorter at the cost of multiuser interference. To see how the decrease of the length of data transmission phase can improve the spectral efficiency, we derive the throughput as well as the spectral efficiency. From the results of analysis, we can show that the 2-step CDMA-based random access approach can have a higher spectral efficiency than conventional 2-step approach with orthogonal channel allocations, which means that the performance of MTC can be improved by successfully transmitting more data packets per unit time using CDMA. This is also confirmed by simulation results. [ABSTRACT FROM AUTHOR]

This paper considers the problem of source coding with side information at the decoder, also called Slepian–Wolf source coding scheme. In practical applications of this coding scheme, the statistical relation between the source and the side information can vary from one data transmission to another, and there is a need to adapt the coding rate depending on the current statistical relation. In this paper, we propose a novel rate-adaptive code construction based on LDPC codes for the Slepian–Wolf source coding scheme. The proposed code design method allows to optimize the code degree distributions at all the considered rates, while minimizing the amount of short cycles in the parity check matrices at all rates. Simulation results show that the proposed method greatly reduces the source coding rate compared to the standard low density parity check accumulated (LDPCA) solution. [ABSTRACT FROM AUTHOR]

Fog radio access network (Fog-RAN), which pushes caching and computing capabilities to the network edge, is capable of efficiently delivering content to users by using carefully designed caching placement and content replacement algorithms. In this paper, the transmission scheme design and coding parameter optimization will be considered for coded caching in Fog-RAN, where the reliability of content delivery, i.e., content outage probability, is used as the performance metric. The problem will be formulated as a complicated multi-objective probabilistic combinatorial optimization. A novel maximum $b$ -matching approach will then be proposed to obtain the Pareto optimal solution with fairness constraint. Based on the fast message passing approach, a distributed algorithm with a low memory usage of $O(M+N)$ is also proposed, where $M$ is the number of users and $N$ is the number of fog access points (Fog-APs). Although it is usually very difficult to derive the closed-form formulas for the optimal solution, the approximation formulas of the content outage probability will also be obtained as a function of coding parameters. The asymptotic optimal coding parameters can then be obtained by defining and deriving the outage exponent region and diversity-multiplexing region. Simulation results will illustrate the accuracy of the theoretical derivations, and verify the outage performance of the proposed approach. Therefore, this paper not only proposes a practical distributed Fog-AP selection algorithm for coded caching but also provides a systematic way to evaluate and optimize the performance of Fog-RANs. [ABSTRACT FROM AUTHOR]

This paper focuses on the design and evaluation of pragmatic schemes for delay-sensitive communication. Specifically, this contribution studies the operation of data links that employ incremental redundancy as a means to shield information bits from the degradation associated with unreliable channels. While this inquiry puts forth a general methodology, exposition centers around erasure channels because they are well suited for analysis. Nevertheless, the goal is to identify both structural properties and design guidelines that are broadly applicable. Conceptually, this paper leverages a methodology, termed sequential differential optimization, aimed at identifying near-optimal block sizes for hybrid ARQ. This technique is applied to erasure channels and it is extended to scenarios where throughput is maximized subject to a constraint on the feedback rate. The analysis shows that the impact of the coding strategy adopted and the propensity of the channel to erase symbols naturally decouple when maximizing throughput. Ultimately, block size selection is informed by approximate distributions on the probability of decoding success at every stage of the incremental transmission process. This novel perspective, which rigorously bridges hybrid automatic repeat request and coding, offers a computationally efficient framework to select code rates and blocklengths for incremental redundancy. These findings are supported through numerical results. [ABSTRACT FROM AUTHOR]

Zero correlation zone (ZCZ) sequence sets and Golay complementary sets (GCSs) have different correlation properties and hence have different engineering applications. A number of constructions of ZCZ sequence sets and GCSs have been proposed, respectively, in the literature. In addition, some ZCZ sequence sets can be constructed from mutually orthogonal GCSs. In this paper, the relationship between GCSs and ZCZ sets is discovered further. We propose a new type of sequence sets which are ZCZ sequence sets and also GCSs. They are called the Golay-ZCZ sequence sets in this paper. Therefore, they have low peak-to-average power ratios when employed in OFDM systems due to the good autocorrelation properties of GCSs. Besides, the Golay-ZCZ sets possess zero autocorrelations and cross-correlations within their ZCZ and hence have the potential application to synchronization. Furthermore, a construction of Golay-ZCZ sequence family with flexible set sizes, various sequence lengths, and large ZCZ widths is proposed in this paper. [ABSTRACT FROM AUTHOR]

Faster-than-Nyquist (FTN) transmission employing antenna polarization multiplexing and higher order modulation (HoM) schemes can significantly increase the spectral efficiency (SE) of the existing wireless backhaul links. However, the benefits of each of these SE enhancement techniques come with a price. While FTN introduces inter-symbol interference, a dual-polarized (DP) transmission suffers from cross-polarization interference (XPI), and HoM makes a communication system vulnerable to phase-noise (PN) distortions. In this paper, we investigate, for the first time, a DP-FTN HoM transmission system. We propose a XPI cancellation and PN mitigation structure, coupled with adaptive decision-feedback equalization or linear precoding, to jointly mitigate interference and accomplish carrier-phase tracking. The DP systems combined with the FTN signaling presented in this paper offer more than 150% increase in SE compared with a single-polarized Nyquist transmission. The effectiveness of the proposed algorithms is demonstrated through computer simulations of a coded DP-FTN microwave communication system in the presence of PN. Numerical results suggest that with the proposed interference cancellation methods, a DP-FTN transmission can yield a 3–5.5-dB performance improvement over an equivalent DP-Nyquist system that employs a higher modulation order to achieve the same data rate. [ABSTRACT FROM AUTHOR]

This paper investigates the design and analysis of minimum mean square error (MMSE) turbo decision feedback equalization (DFE), with expectation propagation (EP), for single carrier modulations. Classical non iterative DFE structures have substantial advantages at high-data rates, even compared with turbo linear equalizers-interference cancellers (LE-IC), hence making turbo DFE-IC schemes an attractive solution. In this paper, we derive an iterative DFE-IC, capitalizing on the use of soft feedback based on expectation propagation, along with the use of prior information for improved filtering and interference cancellation. This turbo iterative DFE-IC significantly outperforms turbo LE-IC, especially at high-spectral efficiency and also exhibits performance improvements over existing DFE-IC variants. The proposed scheme can also be self-iterated, as done in the recent trend on EP-based equalizers, and it is shown to be an attractive alternative to linear self-iterated receivers. For time-varying (TV) filter equalizers, an efficient matrix inversion scheme is also proposed, considerably reducing the computational complexity relative to existing methods. Using finite-length and asymptotic analysis on a severely selective channel, the proposed DFE-IC is shown to achieve higher rates than known alternatives, with better waterfall thresholds and faster convergence, while keeping a similar computational complexity. [ABSTRACT FROM AUTHOR]

This paper analyzes an emerging architecture of cellular network utilizing both planar base stations uniformly distributed in the Euclidean plane and base stations located on roads. An example of this architecture is that where, in addition to conventional planar cellular base stations and users, vehicles also play the role of both base stations and users. A Poisson line process is used to model the road network and, conditionally on the lines, linear Poisson point processes are used to model the vehicles on the roads. The conventional planar base stations and users are modeled by the independent planar Poisson point processes. We use Palm calculus to investigate the statistical properties of a typical user in such a network. Specifically, this paper discusses two different Palm distributions, with respect to the user point processes depending on its type: planar or vehicular. We derive the distance to the nearest base station, the association of the typical users, and the coverage probability of the typical user. Furthermore, we provide a comprehensive characterization of coverage of all possible cellular transmissions in this setting, namely, vehicle-to-vehicle, vehicle-to-infrastructure, infrastructure-to-vehicle, and infrastructure-to-infrastructure. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new adaptive modulation based on the wavelet packet transform, which targets a good resistance against frequency selective channels while avoiding a large PAPR. Classical multi-carrier modulation schemes divide the channel bandwidth into narrowband sub-channels to improve its robustness against frequency selective fading. However, they suffer from the peak-to-average power ratio (PAPR) problem, which occurs due to a random constructive addition of sub-carriers. By contrast, single carrier modulation schemes, where each transmitted symbol fully occupies the bandwidth, are more sensitive to frequency selective environments and less affected by the PAPR problem. In this paper, we show how the bandwidth division can be reconfigurable and adapted to the channel properties, and we provide several examples to prove that the proposed adaptive modulation represents an alternative modulation which is adjustable between two extreme cases: single carrier modulation and classical multi-carrier modulation. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) relay networks are convinced to be a significant complement to terrestrial infrastructures to provide robust network capacity. However, most of the existing works either considered enhanced mobile broadband (eMBB) payload communication or ultra-reliable and low latency communications (URLLC) control information communication. In this paper, we investigate resource allocation for the eMBB payload and URLLC control information communication multiplexing in a multi-UAV relay network. We firstly propose a multi-UAV relay model comprehensively considering path loss, small-scale channel fading and different quality of service requirements of eMBB and URLLC communications. Then we formulate the multiplexing problem as a joint user association, bandwidth and transmit power optimization problem to improve total transmission data rate and reduce power consumption. The solution of this problem is challenging due to different capacity characteristics of eMBB and URLLC communications, the coupling of continuous variables and integer variables, and the non-convexity. To mitigate these challenges, we equivalently decompose the original optimization problem into a URLLC problem and an eMBB problem. For the URLLC problem, we derive closed-form expressions of the optimal bandwidth and transmit power. For the eMBB problem, we develop an iterative solution framework of alternatively optimizing user association, bandwidth and transmit power. [ABSTRACT FROM AUTHOR]

This paper focuses on the non-coherent detection in ambient backscatter communication, which is highly appealing for systems where the trade-off between signaling overhead and the actual data transmission is very critical. Modeling the time-selective fading channel as a first-order autoregressive (AR) process, we propose a new receiver architecture based on the direct averaging of the received signal samples for detection, which departs significantly from the energy averaging-based receivers considered in the literature. For the proposed setup, we characterize the exact asymptotic bit error rate (BER) for both single-antenna (SA) and multi-antenna (MA) receivers, and demonstrate the robustness of the new architecture to timing errors. Our results demonstrate that while the direct-link (DL) interference from the ambient power source leads to a BER floor in the SA receiver, the MA receiver can remove this interference by estimating the angle of arrival (AoA) of the DL. The analysis further quantifies the effect of improved angular resolution on the BER as a function of the number of receive antennas. A key intermediate result of our analysis is the derivation of a new concentration result for a general sum sequence that is central to the derivation of the conditional distributions of the received signal. [ABSTRACT FROM AUTHOR]

In a wirelessly-powered communication network (WPCN), an energy access point (E-AP) supplies the energy needs of the network nodes through radio frequency wave transmission, and the nodes store their received energy in their batteries for possible data transmission. In this paper, we propose an online control policy for energy transfer from the E-AP to the wireless nodes and for data transfer among the nodes. With our proposed control policy, all data queues of the nodes are stable, while the average energy consumption of the network is shown to be within a bounded gap of the minimum energy required for stabilizing the network. Our proposed policy is designed using a quadratic Lyapunov function to capture the limitations on the energy consumption of the nodes imposed by their battery levels. We show that under the proposed control policy, the backlog level in the data queues and the stored energy level in the batteries fluctuate in small intervals around some constant levels. Consequently, by imposing a negligible average data drop rate, the data buffer size and the battery capacity of the nodes can be significantly reduced. [ABSTRACT FROM AUTHOR]

Cross-technology Communication (CTC) is a promising paradigm for efficient coordination and cooperation among heterogeneous wireless technologies. Recent advances in physical-layer CTC (PHY-CTC) approaches the standards’ maximum transmission rate by exploring PHY-layer signal features. However, due to the lack of reliable feedback, current PHY-CTC technologies can hardly ensure transmission reliability. This paper presents RAP (Reliable Acknowledged PHY-CTC), a bidirectional CTC design with reliable PHY-CTC feedback. First, we present a novel PHY-CTC technique to efficiently establish a reliable feedback channel (e.g., ACKs or NACKs). Then, based on the feedback, we propose a joint intra-packet coding and inter-packet coding scheme to improve the reliability of CTC. Finally, we present an on-demand data (re)transmission scheme to support unicast, multicast and broadcast more efficiently. We implement and evaluate RAP on USRP N210 with IEEE 802.11g PHY (WiFi) and commodity ZigBee devices. The experiment results show RAP achieves reliable data transmission (>99% packet reception rate (PRR)) and high throughput (over 35kbps) under a wide range of scenarios. [ABSTRACT FROM AUTHOR]

A common model for transmission over wireless links is that of a multiantenna system affected by an additive interfering signal. In some scenarios of interest, such as when the interferer is located close to the transmitter and performs retransmission, interference may be learned by the transmitter, but remain unknown at the receiver. In this case, it is well known that, if transmitter and receiver have perfect channel state information (CSI), then a technique called Dirty Paper Coding (DPC) is able to fully mitigate the interference. This paper studies the impact of imperfect CSI on a multiple-input multiple-output (MIMO) system with interference and compares the performance of DPC with that of a scheme where interference is decoded at the receiver, which we refer to as beamforming with joint decoding (BF-JD). Unlike DPC, which models the interference as an "unstructured" random process, BF-JD exploits the fact that the interfering signal is a codeword of the interferer's codebook. It is demonstrated by analysis and numerical results that BF-JD provides advantages over DPC when CSI is imperfect at the transmitter but perfect at the receiver, whereas this is not true for the case of imperfect CSI at both transmitter and receiver. [ABSTRACT FROM AUTHOR]

We present a symbol-by-symbol approach to the problem of canceling known interference at the transmitter in a communication system. In the envisioned system, the modulator maps an information symbol (taken from a finite alphabet) and an interference symbol (from the complex field) onto a transmitted constellation point. Our scheme is based on joint optimization of a modulator and demodulator, subject to a constraint on the average transmit power. The demodulator picks the information symbol (as a function of the received symbol) that minimizes the average error probability. We emphasize that our focus is on transmission in a single (complex) dimension, and hence the proposed technique is a "modulation" rather than a "coding" scheme. We illustrate that the new scheme outperforms Tomlinson-Harashima precoding, which is a classical but suboptimal solution to the one-dimensional known-interference precoding problem. In our simulations, the new approach is able to perform close to the no-interference bound. [ABSTRACT FROM AUTHOR]

In recent years, a large number of smart devices will be connected in Internet of Things (IoT) using an ad hoc network, which needs more frequency spectra. The cognitive radio (CR) technology can improve spectrum utilization in an opportunistic communication manner for IoT, forming a promising paradigm known as cognitive radio ad hoc networks, CRAHNs. However, dynamic spectrum availability and mobile devices/persons make it difficult to develop an efficient data transmission scheme for CRAHNs under an obstacle environment. Opportunistic routing can leverage the broadcast nature of wireless channels to enhance network performance. Inspired by this, in this paper, we propose an Obstacle aware Opportunistic Data Transmission scheme (OODT) in CRAHNs from a computational geometry perspective, considering energy efficiency and social features. In the proposed scheme, we exploit a new routing metric, which is based on an obstacle avoiding algorithm using a polygon boundary 1-searcher technology, and an auction model for selecting forwarding candidates. In addition, we prove that the candidate selection problem is NP-hard and propose a heuristic algorithm for candidate selection. The simulation results show that the proposed scheme can achieve better performance than existing schemes. [ABSTRACT FROM AUTHOR]

This paper presents an analytical framework which lays the foundation for distributed massive multiple-input multiple-output (MIMO) supported wireless power transfer for wearable devices. In our approach, we consider multiple users, each wearing a number of wireless sensors along with one body worn hub which acts as a relay to forward information from the on-body sensors to nearby access points (APs). Each AP is equipped with a large number of antennas and is not only responsible for receiving data sent from the hubs, but also supplying wireless power to them. Interaction between hubs and APs is not exclusive to a single pairing, with APs assigned to supply energy to and receive data from more than one hub. More precisely, APs perform the downlink energy transmission and the uplink data transmission using maximum-ratio combining. Analytical approximations of the outage probability and spectral efficiency are derived. Based on these analytical results, two modes of operation are investigated. These are outage probability prioritized and spectral efficiency prioritized. For each mode, max-min power controls are proposed to ensure a uniformly good service throughout the area of coverage. By contrasting with the IEEE 802.15.6 standard, the numerical results illustrate that while using collocated massive MIMO may provide unsatisfactory performance, the distributed setting shows much promise for enabling wireless power transfer for wearable devices. [ABSTRACT FROM AUTHOR]