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Imperfect Channel State Information at the Transmitter (CSIT) is inevitable in modern wireless communication networks, and results in severe multi-user interference in multi-antenna Broadcast Channel (BC). While the capacity of multi-antenna (Gaussian) BC with perfect CSIT is known and achieved by Dirty Paper Coding (DPC), the capacity and the capacity-achieving strategy of multi-antenna BC with imperfect CSIT remain unknown. Conventional approaches therefore rely on applying communication strategies designed for perfect CSIT to the imperfect CSIT setting. In this work, we break this conventional routine and make two major contributions. First, we show that linearly precoded Rate-Splitting (RS), relying on the split of messages into common and private parts and linear precoding at the transmitter, and successive interference cancellation at the receivers, can achieve larger rate region than DPC in multi-antenna BC with partial CSIT. Second, we propose a novel scheme, denoted as Dirty Paper Coded Rate-Splitting (DPCRS), that relies on RS to split the user messages into common and private parts, and DPC to encode the private parts. We show that the rate region of DPCRS in Multiple-Input Single-Output (MISO) BC with partial CSIT is enlarged beyond that of conventional DPC and that of linearly precoded RS. Gaining benefits from the capability of RS to partially decode the interference and partially treat interference as noise, DPCRS is less sensitive to CSIT inaccuracies, networks loads and user deployments compared with DPC and other existing transmission strategies. [ABSTRACT FROM AUTHOR]

Terahertz (THz) band communications are envisioned as a key technology for 6G and Beyond. As a fundamental wireless infrastructure, THz communication can boost abundant promising applications. In 2014, our team published two comprehensive roadmaps for the development and progress of THz communication networks, which helped the research community to start research on this subject afterwards. The topic of THz communications became very important and appealing to the research community due to 6G wireless systems design and development in recent years. Many papers are getting published covering different aspects of wireless systems using the THz band. With this paper, our aim is looking back to the last decade and revisiting the old problems and pointing out what has been achieved in the research community so far. Furthermore, in this paper, open challenges and new research directions still to be investigated for the THz band communication systems are presented, by covering diverse topics ranging from devices, channel behavior, communication and networking, to physical testbeds and demonstration systems. The key aspects presented in this paper will enable THz communications as a pillar of 6G and Beyond wireless systems in the next decade. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of joint beam selection and link activation across a set of communication pairs to effectively control the interference between communication pairs via inactivating part communication pairs in ultra-dense device-to-device (D2D) mmWave communication networks. The resulting optimization problem is formulated as an integer programming problem that is nonconvex and NP-hard. Consequently, the global optimal solution, even the local optimal solution, cannot be generally obtained. To overcome this challenge, this paper resorts to design a deep learning architecture based on graph neural network to finish the joint beam selection and link activation, with taking the network topology information into account. Meanwhile, we present an unsupervised Lagrangian dual learning framework to train the parameters of the GBLinks model. Numerical results show that the proposed GBLinks model can converge to a stable point with the number of iterations increases, in terms of the weighted sum rate. Furthermore, the GBLinks model can reach near-optimal solutions through comparing with the exhaustive scheme in small-scale ultra-dense D2D mmWave communication networks and outperforms GreedyNoSched and the SCA-based method. It also shows that the GBLinks model can generalize to varying network densities and network coverage regions of ultra-dense D2D mmWave communication networks. [ABSTRACT FROM AUTHOR]

A hybrid communication network with a common analog source signal and independent digital data streams at the transmitters of a multiple access network is considered. The receiver has to estimate the analog signal samples with a given fidelity, and decode the digital streams with a low error probability. The main goal of this paper is to characterize the optimal tradeoff between the mean-squared error distortion in source estimation and the data rates available to each user. To this end, we consider a Gaussian multiple access channel (GMAC) setup with additive state, where the state is nothing but a scaled version of the source process itself. The state process is assumed to be non-causally available to all the transmitting nodes. The problem now becomes that of the joint state estimation and message communication in a GMAC with state. We provide a complete characterization of the optimal distortion-rate tradeoff for an $N$ —sender GMAC. Our results show that, similar to the single-user results, it is optimal to amplify the state using uncoded transmissions, whereas the digital streams are superposed using appropriate Gaussian codebooks in conjunction with dirty paper coding (DPC). Since the variance of the additive state is controlled by a scaling factor in our model, we also recover the results for communicating a common source and independent messages over a GMAC without state as a special case. [ABSTRACT FROM AUTHOR]

The reconfigurable intelligent surface (RIS), which consists of many low-cost reflecting elements, can enhance the reception of the desired signal and suppress the interference. Considering the above advantages, this paper investigates the RIS-assisted wireless communication in the presence of an interferer, where a receiver receives the desired signal and interference from a transmitter and an interferer, respectively, and the RIS is deployed to assist this system. First, an interference-limited channel capacity maximization problem is formulated, and a numerical algorithm based on the fraction programming and optimality conditions is proposed to obtain the optimal solution. Then, this paper shows the upper boundary of the maximal capacity with interference and discusses what kind of channel conditions can achieve the upper boundary and the corresponding optimal phase shifts. Next, this paper analyzes the asymptotic behaviors of the maximal capacity in the scenarios that some or all of the number of reflecting elements, antennas at the transmitter, and interferer go to infinity. Finally, this paper generalizes the above results to the multiple interferers scenario. [ABSTRACT FROM AUTHOR]

This paper presents the design and bit error rate (BER) analysis of a phase-independent non-orthogonal multiple access (NOMA) system. The proposed NOMA system can utilize amplitude-coherent detection (ACD) which requires only the channel amplitude for equalization purposes. In what follows, three different designs for realizing the detection of the proposed NOMA are investigated. One is based on the maximum likelihood (ML) principle, while the other two are based on successive interference cancellation (SIC). Closed-form expressions for the BER of all detectors are derived and compared with the BER of the coherent ML detector. The obtained results, which are corroborated by simulations, demonstrate that, in most scenarios, the BER is dominated by multiuser interference rather than the absence of the channel phase information. Consequently, the BER using ML and ACD are comparable for various cases of interest. The paper also shows that the SIC detector is just an alternative approach to realize the ML detector, and hence, both detectors provide the same BER performance. [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 prospects of using a Reconfigurable Intelligent Surface (RIS) to aid wireless communication systems have recently received much attention from academia and industry. Most papers make theoretical studies based on elementary models, while the prototyping of RIS-aided wireless communication and real-world field trials are scarce. In this paper, we describe a new RIS prototype consisting of 1100 controllable elements working at 5.8 GHz band. We propose an efficient algorithm for configuring the RIS over the air by exploiting the geometrical array properties and a practical receiver-RIS feedback link. In our indoor test, where the transmitter and receiver are separated by a 30 cm thick concrete wall, our RIS prototype provides a 26 dB power gain compared to the baseline case where the RIS is replaced by a copper plate. A 27 dB power gain was observed in the short-distance outdoor measurement. We also carried out long-distance measurements and successfully transmitted a 32 Mbps data stream over 500 m. A 1080p video was live-streamed and it only played smoothly when the RIS was utilized. The power consumption of the RIS is around 1 W. Our paper is vivid proof that the RIS is a very promising technology for future wireless communications. [ABSTRACT FROM AUTHOR]

This paper is concerned with the security problem of Time of Arrival (ToA) based localization schemes in a wireless sensor network (WSN) with multiple attackers and this paper focuses on defending against external attacks, especially under cooperative external attackers. The prior scheme for defending against the attacks in the localization scheme often introduce high communication overhead and their security relies on the capability of the attackers. In this paper, we propose a lightweight secure ToA-based localization scheme in a WSN by exploiting the noise feature caused by external distance attacks. In comparison with the prior scheme, our scheme provides lower communication overhead and a higher level of security. We theoretically analyze the performance of the proposed scheme over fading channels and derive the closed-form expressions. We implemented our scheme and conducted extensive performance comparisons through simulations. Our experimental results show that the closed-form expressions for the detection performance perfectly match with their simulation results as we expected. The communication overhead of the proposed scheme is saved by 72.8% than that of the prior scheme for different numbers of anchors and is independent of the times of measurements. [ABSTRACT FROM AUTHOR]

This paper derives the asymptotic distribution of the normalized $k$ -th maximum order statistics of a sequence of non-central chi-square random variables with non-identical non-centrality parameters. We demonstrate the utility of these results in characterizing the signal-to-noise ratio in three different applications in wireless communication systems where the statistics of the $k$ -th maximum channel power over Rician fading links are of interest. Furthermore, we derive simple expressions for the asymptotic outage probability, average throughput, achievable throughput, and average bit error probability. The proposed results are validated via extensive Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

We consider the application of the factor graph framework for symbol detection on linear inter-symbol interference channels. Based on the Ungerboeck observation model, a detection algorithm with appealing complexity properties can be derived. However, since the underlying factor graph contains cycles, the sum-product algorithm (SPA) yields a suboptimal algorithm. In this paper, we develop and evaluate efficient strategies to improve the performance of the factor graph-based symbol detection by means of neural enhancement. In particular, we consider neural belief propagation and generalizations of the factor nodes as an effective way to mitigate the effect of cycles within the factor graph. By applying a generic preprocessor to the channel output, we propose a simple technique to vary the underlying factor graph in every SPA iteration. Using this dynamic factor graph transition, we intend to preserve the extrinsic nature of the SPA messages which is otherwise impaired due to cycles. Simulation results show that the proposed methods can massively improve the detection performance, even approaching the maximum a posteriori performance for various transmission scenarios, while preserving a complexity which is linear in both the block length and the channel memory. [ABSTRACT FROM AUTHOR]

The use of 1-bit analog-to-digital converters (ADCs) is seen as a promising approach to significantly reduce the power consumption and hardware cost of multiple-input multiple-output (MIMO) receivers. However, the nonlinear distortion due to 1-bit quantization fundamentally changes the optimal communication strategy and also imposes a capacity penalty to the system. In this paper, the capacity of a Gaussian MIMO channel in which the antenna outputs are processed by an analog linear combiner and then quantized by a set of zero threshold ADCs is studied. A new capacity upper bound for the zero threshold case is established that is tighter than the bounds available in the literature. In addition, we propose an achievability scheme which configures the analog combiner to create parallel Gaussian channels with phase quantization at the output. Under this class of analog combiners, an algorithm is presented that identifies the analog combiner and input distribution that maximize the achievable rate. Numerical results are provided showing that the rate of the achievability scheme is tight in the low signal-to-noise ratio (SNR) regime. Finally, a new 1-bit MIMO receiver architecture which employs analog temporal and spatial processing is proposed. The proposed receiver attains the capacity in the high SNR regime. [ABSTRACT FROM AUTHOR]

This paper studies cached-aided multicast transmissions in fronthaul fog radio access networks (F-RANs). While index coding and cached-aided non-orthogonal multiple access (NOMA) are techniques commonly used for utilizing cache contents to save transmit energy, there is a lack of general framework to integrate them. This work proposes index-coded NOMA and dynamic coded-NOMA to investigate energy performance of the integration of index coding and NOMA under whole-file and subfile caching, respectively. Besides, dynamic cache space allocation is applied to both caching schemes, which allocates cache sizes to the fog access points (F-APs) according to their large-scale channel conditions. For index-coded NOMA, the general grouping problem is proved to be NP-hard and optimal solutions for some special cases are given. Furthermore, efficient heuristic grouping algorithms are proposed. For dynamic coded-NOMA, we obtain the closed-form minimum transmit energy. The numerical results validate the good performance of our proposed algorithms. Index-coded NOMA and dynamic coded-NOMA have comparable performance and both of them save much energy than the existing schemes. When there are 12 F-APs under small-cache scenarios, index-coded NOMA saves energy by 70.3% compared to traditional NOMA. [ABSTRACT FROM AUTHOR]

Mutualistic cooperative ambient backscatter communications (AmBC) have been proposed to improve the spectrum and energy efficiencies of Internet-of-Things (IoT) systems, where a primary link (from a primary transmitter to a primary receiver) and an AmBC link (from an IoT device to the same primary receiver) form a mutualism relationship. We note that hardware impairments (HIs), which are unavoidable in practical systems and may significantly affect the transmission rates of the primary and AmBC links and their mutualism relationships, have been largely ignored in the study of mutualistic cooperative AmBC networks. In this paper, we study a mutualistic cooperative AmBC network with HIs at all the active transceivers and a non-linear energy harvesting circuit at each IoT device. We derive closed-form rate expressions for both the AmBC and primary links and theoretically prove that the mutualism relationship between the AmBC and primary links is maintained under HIs, i.e., the rate of the primary link in the mutualistic cooperative AmBC network is still higher than that without the AmBC link. To maximize the weighted sum rate of all links in a cooperative AmBC network under HIs, we propose two resource allocation schemes for two scenarios with a single link and multiple AmBC links, respectively. For the single AmBC link case, we derive the optimal transmit power of the primary transmitter and the optimal power reflection coefficient of the IoT device in closed forms. For the scenario with multiple AmBC links, the weighted-sum-rate maximization problem is transformed into a convex one and solved with convex optimization tools. Computer simulations validate our theoretical results and that our proposed schemes outperform the benchmark schemes in terms of the weighted sum rate. [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]

In this paper, we present a low-complexity recursive approach for massive and scalable code-domain nonorthogonal multiple access (NOMA) with applications to emerging low-capacity scenarios. The problem definition in this paper is inspired by three major requirements of the next generations of wireless networks. Firstly, the proposed scheme is particularly beneficial in low-capacity regimes which is important in practical scenarios of utmost interest such as the Internet-of-Things (IoT) and massive machine-type communication (mMTC). Secondly, we employ code-domain NOMA to efficiently share the scarce common resources among the users. Finally, the proposed recursive approach enables code-domain NOMA with low-complexity detection algorithms that are scalable with the number of users to satisfy the requirements of massive connectivity. To this end, we propose a novel encoding and decoding scheme for code-domain NOMA based on factorizing the pattern matrix, for assigning the available resource elements to the users, as the Kronecker product of several smaller factor matrices. As a result, both the pattern matrix design at the transmitter side and the mixed symbols’ detection at the receiver side can be performed over matrices with dimensions that are much smaller than the overall pattern matrix. Consequently, this leads to significant reduction in both the complexity and the latency of the detection. We present the detection algorithm for the general case of factor matrices. The proposed algorithm involves several recursions each involving certain sets of equations corresponding to a certain factor matrix. We then characterize the system performance in terms of average sum rate, latency, and detection complexity. Our latency and complexity analysis confirm the superiority of our proposed scheme in enabling large pattern matrices. Moreover, our numerical results for the average sum rate show that the proposed scheme provides better performance compared to straightforward code-domain NOMA with comparable complexity, especially at low-capacity regimes. [ABSTRACT FROM AUTHOR]

Reactive jammers, which start attacking upon sensing legitimate transmissions, are serious threats to wireless communications. Conventional anti-jamming methods such as frequency hopping-based anti-jamming schemes are not effective against reactive jammers, especially the agile ones that jam immediately after sensing transmissions. Deceiving-based anti-jamming methods have a great potential in harnessing reactive jammers and securing communication channels for legitimate users. However, in deceiving-based anti-jamming methods, reaching the optimal power and channel allocation is complicated due to the unavailability of the jammers’ channel information. In this paper, we propose deceiving-based anti-jamming schemes against reactive jammers employing reinforcement learning. Moreover, we consider both cases where a reactive jammer can jam a channel or all the channels utilized by legitimate users. In the latter case, we model the interaction between users and the jammer as a non-cooperative Stackelberg game and prove equilibrium. In addition, we study different scenarios where the interacting environment is static or dynamic in terms of channel gains. Simulation results show that in static environments, the proposed methods achieve the optimal values of the total received power and Signal-to-interference-plus-noise ratio with an accuracy of 95%. Moreover, in dynamic environments, the proposed methods provide high performance in terms of the considered evaluation metrics. [ABSTRACT FROM AUTHOR]

The components with molecular communication (MC) functionalities can bring an opportunity for emerging applications in fields from personal healthcare to modern industry. In this paper, we propose the designs of the microfluidic transmitter and receiver with quadruple concentration shift keying (QCSK) modulation and demodulation functionalities. To do so, we first present an AND gate design, and then apply it to the QCSK transmitter and receiver design. The QCSK transmitter is capable of modulating two input signals to four different concentration levels, and the QCSK receiver can demodulate a received signal to two outputs. More importantly, we also establish a mathematical framework to theoretically characterize our proposed microfluidic circuits. Based on this, we first derive the output concentration distribution of our proposed AND gate design, and provide the insight into the selection of design parameters to ensure an exhibition of desired behavior. We further derive the output concentration distributions of the QCSK transmitter and receiver. Simulation results obtained in COMSOL Multiphysics not only show the desired behavior of all the proposed microfluidic circuits, but also demonstrate the accuracy of the proposed mathematical framework. [ABSTRACT FROM AUTHOR]

In this paper, we study a quantized feedback scheme to maximize the goodput of a finite blocklength communication scenario over a quasi-static fading channel. It is assumed that the receiver has perfect channel state information (CSI) and sends back the CSI to the transmitter over a resolution-limited error-free feedback channel. With this partial CSI, the transmitter is supposed to select the optimum transmission rate, such that it maximizes the overall goodput of the communication system. This problem has been studied for the asymptotic blocklength regime, however, no solution has so far been presented for finite blocklength. Here, we study this problem in two cases: with and without constraint on reliability. We first formulate the optimization problems and analytically solve them. Iterative algorithms that successfully exploit the system parameters for both cases are presented. It is shown that although the achievable maximum goodput decreases with shorter blocklengths and higher reliability requirements, significant improvement can be achieved even with coarsely quantized feedback schemes. [ABSTRACT FROM AUTHOR]

In this paper, the role of feedback in two-way full-duplex Gaussian channel (TW-FD-GC) is revisited. First, we propose a practical coding scheme for the TW-FD-GC, which is based on the noisy type of the well-known Schalkwijk-Kailath (SK) feedback scheme. We show that though this scheme cannot achieve the capacity of the TW-FD-GC, the codeword length that achieves desired decoding error probability is extremely short. Then, we further prove that the proposed scheme is secure by itself, i.e., the achievable rate region of the proposed scheme is also an achievable secrecy rate region of the two-way full-duplex Gaussian wiretap channel (TW-FD-GWTC). In addition, for the TW-FD-GWTC, numerical result shows that the secrecy sum rate of our proposed scheme can be as large as those achieved by existing schemes in the literature for some cases. Next, we extend the proposed scheme to the TW-FD-GC with Gaussian state interference non-causally known by the corresponding transmitter. We show that the interference can be perfectly canceled by this extended scheme. Finally, we prove that this extended scheme is also secure by itself, and numerical result shows that this extended scheme may perform better than the existing ones in the literature. [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]

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM), a fundamental transmission scheme, promises high throughput and robustness against multipath fading. However, these benefits rely on the efficient detection strategy at the receiver and come at the expense of the extra bandwidth consumed by the cyclic prefix (CP). We use the iterative orthogonal approximate message passing (OAMP) algorithm in this paper as the prototype of the detector because of its remarkable potential for interference suppression. However, OAMP is computationally expensive for the matrix inversion per iteration. We replace the matrix inversion with the conjugate gradient (CG) method to reduce the complexity of OAMP. We further unfold the CG-based OAMP algorithm into a network and tune the critical parameters through deep learning (DL) to enhance detection performance. Simulation results and complexity analysis show that the proposed scheme has significant gain over other iterative detection methods and exhibits comparable performance to the state-of-the-art DL-based detector at a reduced computational cost. Furthermore, we design a highly efficient CP-free MIMO-OFDM receiver architecture to remove the CP overhead. This architecture first eliminates the intersymbol interference by buffering the previously recovered data and then detects the signal using the proposed detector. Numerical experiments demonstrate that the designed receiver offers a higher spectral efficiency than traditional receivers. Finally, over-the-air tests verify the effectiveness and robustness of the proposed scheme in realistic environments. [ABSTRACT FROM AUTHOR]

Over the past few years, the use of wireless sensor networks in a range of Internet of Things (IoT) scenarios has grown in popularity. Since IoT sensor devices have restricted battery power, a proper IoT data aggregation approach is crucial to prolong the network lifetime. To this end, current approaches typically form a virtual aggregation backbone based on a connected dominating set or maximal independent set to utilize independent transmissions of dominators. However, they usually have a fairly long aggregation delay because the dominators become bottlenecks for receiving data from all dominatees. The problem of time-efficient data aggregation in multichannel duty-cycled IoT sensor networks is analyzed in this paper. We propose a novel aggregation approach, named LInk-delay-aware REinforcement (LIRE), leveraging active slots of sensors to explore a routing structure with pipeline links, then scheduling all transmissions in a bottom-up manner. The reinforcement schedule accelerates the aggregation by exploiting unused channels and time slots left off at every scheduling round. LIRE is evaluated in a variety of simulation scenarios through theoretical analysis and performance comparisons with a state-of-the-art scheme. The simulation results show that LIRE reduces more than 80% aggregation delay compared to the existing scheme. [ABSTRACT FROM AUTHOR]

We investigate multiuser detection under uplink asynchronous scenario, where the triangular successive interference cancellation (T-SIC) detection scheme is exploited. As the existing analysis was conducted under some ideal assumptions for simplicity, the asynchronous scenario is analyzed under rigorous assumptions in this paper so that important insights are revealed for practical systems. Specifically, the average symbol error rate (SER) formulas are derived for a two-user system with arbitrary $M$ -ary quadrature amplitude modulation ($M$ -QAM) over Rayleigh fading channels. These solutions are shown to have higher accuracies compared to the existing solutions. Furthermore, a novel iterative detection algorithm is proposed, i.e., the parallel T-SIC method, which is more efficient and effective compared to the iterative T-SIC method. Insightful discussion is conducted in terms of the potentials of the concerned iterative detection method. Simulation results show that the most significant improvement of the iterative detection reflects on the SER for the strongest user, and the reduction is always within 50% of the SER compared to the primary detection. The gains obtained by the iterative detection is negligible for higher order $M$ -QAM cases. [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]

Next-generation satellite systems targeting multi-Terabit-per-second throughput require surmounting layers of design challenges. For feeder links, extremely high frequency (EHF) band is desired to overcome spectrum limitations and reduce equipment size. Multiple gateways are utilized to aggregate their bandwidths and serve as site diversity, mitigating the increased susceptibility of the EHF band to atmospheric attenuation. Toward this, multiple-input multiple-output (MIMO) technology is well suited for feeder links that share the same time, frequency, and polarization resources. This paper provides novel extension of MIMO-enabled feeder links when clustering more than two gateways and mounting more than two antennas onboard geostationary multibeam satellite, exploiting line-of-sight MIMO on uplinks and downlinks. Arsenal of countermeasures against inter-antenna interference and weather impairments is designed to maximize gains in signal-to-noise ratio, spatial multiplexing, and spatial diversity. Comparisons between offered sum rates and theoretical MIMO capacity are provided when gateway clusters form linear versus circular patterns. Methodology for gateway diversity is developed and analyzed when deploying redundant MIMO feeder links that handle rerouted traffic. Algorithms for ground-based channel state information (CSI) acquisition are designed and implemented in receiver architecture that tackles strong practical impairments. Numerical studies reveal that MIMO-enabled feeder links offer greatly enhanced overall network availability compared with state-of-the-art single-input single-output (SISO) solutions. [ABSTRACT FROM AUTHOR]

In this paper, we consider a mobile molecular communication (MC) system consisting of two mobile nanomachines, a transmitter and a receiver, propelled by a positive drift velocity and Brownian motion in a realistic blood-vessel-type flow regime. Considering the nonlinear movement of the nanomachines, an extended Kalman filter is employed to estimate the distance from the transmitter. Furthermore, based on the predicted distance, to keep the number of received molecules for bit 1 at a stable level, we employ power control on the number of transmitted molecules based on the distance between the transmitter and the receiver and the residual molecules in the channel from the previous transmission. Finally, the optimal detection threshold is obtained by minimizing the error probability. It is verified that a fixed optimal detection threshold can be effective for the power control scheme in the mobile MC. The bit error rate (BER) performance of our scheme is verified via simulation results. [ABSTRACT FROM AUTHOR]

The increasing demands of power supply and data rate for mobile devices promote the research of simultaneous wireless information and power transfer (SWIPT). Optical SWIPT, as known as simultaneous light information and power transfer (SLIPT), has the potential for providing high-capacity communication and high-power wireless charging. However, SLIPT technologies based on light-emitting diodes have low efficiency due to energy dissipation over the air. Laser-based SLIPT technologies need strict positioning accuracy and scanning resolution, which may lead to the increase of costs and complexity. In this paper, we propose a mobile SLIPT scheme based on spatially separated laser resonator (SSLR) and intra-cavity second harmonic generation. The power and data are transferred via separated frequencies, while they share the same self-aligned resonant beam path, without the needs of receiver positioning and beam steering. We establish the analysis model of the resonant beam power and its second harmonic power. Numerical results show that the proposed system can achieve watt-level battery charging power and above 10-bit/s/Hz achievable rate at 6-m distance, which satisfies the requirements of most indoor mobile devices. [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]

Computation over multiple access channels (CoMAC) has been proposed to solve the problem of spectrum scarcity in wireless networks, which combines communication and computation efficiently using the superposition property of wireless channels. In this paper, we consider a multi-cluster CoMAC network, whose performance is affected by the inter-cluster interference and the non-uniform fading. To minimize the sum mean squared error of signals aggregated at different fusion centers (FCs), we propose a transceiver design for multi-cluster CoMAC. Specifically, we adopt a uniform-forcing transmitter design to formulate the receiver design as a quadratic sum-of-ratios problem with nonconvex quadratic constraints. Then, we propose a branch-and-bound algorithm to find its optimal solution with a given error tolerance. To solve the problem in a decentralized way, we develop a distributed algorithm based on the primal decomposition theory. Each subproblem is solved by using the successive convex approximation method. Further combining Lagrange duality, we derive the optimal solution structure of each subproblem, based on which we can find the solution with lower complexity. Simulation results demonstrate the effectiveness of the proposed distributed transceiver design. [ABSTRACT FROM AUTHOR]

The fact that the millimeter-wave (mmWave) multiple-input multiple-output (MIMO) channel has sparse support in the spatial domain has motivated recent compressed sensing (CS)-based mmWave channel estimation methods, where the angles of arrivals (AoAs) and angles of departures (AoDs) are quantized using angle dictionary matrices. However, the existing CS-based methods usually obtain the estimation result through one-stage channel sounding that have two limitations: (i) the requirement of large-dimensional dictionary and (ii) unresolvable quantization error. These two drawbacks are irreconcilable; improvement of the one implies deterioration of the other. To address these challenges, we propose, in this paper, a two-stage method to estimate the AoAs and AoDs of mmWave channels. In the proposed method, the channel estimation task is divided into two stages, Stage I and Stage II. Specifically, in Stage I, the AoAs are estimated by solving a multiple measurement vectors (MMV) problem. In Stage II, based on the estimated AoAs, the receive sounders are designed to estimate AoDs. The dimension of the angle dictionary in each stage can be reduced, which in turn reduces the computational complexity substantially. We then analyze the successful recovery probability (SRP) of the proposed method, revealing the superiority of the proposed framework over the existing one-stage CS-based methods. We further enhance the reconstruction performance by performing resource allocation between the two stages. We also overcome the unresolvable quantization error issue present in the prior techniques by applying the atomic norm minimization method to each stage of the proposed two-stage approach. The simulation results illustrate the substantially improved performance with low complexity of the proposed two-stage method. [ABSTRACT FROM AUTHOR]

In this paper, we consider precoding and receiving matrices optimization for a two-hop amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay system with a decision feedback equalizer (DFE) at the destination node in the presence of the direct source-destination link. By adopting the minimum mean-squared error (MMSE) criterion, we develop two new transceiver design algorithms for such a system. The first one employs an iterative procedure to design the source, relay, feed-forward, and feedback matrices. The second algorithm is a non-iterative suboptimal approach which decomposes the optimization problem into two tractable subproblems and obtains the source and relay precoding matrices by solving the two subproblems sequentially. Simulation results validate the better MSE and bit-error-rate (BER) performance of the proposed algorithms and show that the non-iterative suboptimal method has a negligible performance loss when the ratio of the source node transmission power to the relay node transmission power is small. In addition, the computational complexity analysis suggests that the second algorithm and one iteration of the first algorithm have the same order of complexity. As the first algorithm typically converges within a few iterations, both proposed algorithms exhibit a low complexity order. [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]

In this paper, a new receiver design based on basis expansion model (BEM) orthogonal time frequency space (OTFS) is presented for high-mobility communications with Doppler-spread channel. By deriving an analytical BEM OTFS system model, a low-order generalized complex exponential BEM (GCE-BEM) aided rough channel estimation is proposed at the initial stage with low pilot overhead, followed by equalization. Then, the refinement of channel estimation and equalization is conducted iteratively, in which a high-resolution GCE-BEM model with a large BEM order is adopted and the detected data symbols are exploited as pseudo-pilots, leading to higher estimation accuracy. Simulation results show that the proposed BEM OTFS receiver significantly outperforms the existing OTFS receivers in terms of the mean square error (MSE) of channel estimation and bit error rate (BER), while featuring low pilot overhead. Results also show the near-optimal performance of the novel solution, i.e., achieved BER is very close to the case of perfect channel estimation. The theoretical lower bound on MSE of channel estimation is derived to verify the effectiveness of the proposed BEM OTFS receiver, which is shown to be close to simulation results. [ABSTRACT FROM AUTHOR]

This paper studies an intelligent reflecting surface (IRS)-assisted wireless-powered communication network (WPCN), where a hybrid access point (HAP) broadcasts energy signals to multiple devices for their energy harvesting in the downlink (DL) and then the devices use the harvested energy to transmit information signals to the HAP in the uplink (UL) with the help of an IRS. In particular, we propose three types of IRS beamforming configurations, namely fully dynamic IRS beamforming (FDBF), partially dynamic IRS beamforming (PDBF), and static IRS beamforming (SBF), to strike a balance between the system performance and signaling overhead as well as implementation complexity. Moreover, we adopt a practical non-linear energy harvesting (EH) model, and leverage a power-splitting (PS) EH receiver architecture with multiple rectifiers to avoid the input radio frequency power to get stuck into the saturation regime. We aim to minimize the transmit energy consumption at the HAP by jointly optimizing the DL/UL time allocation, the HAP/devices transmit power, the PS factor, and IRS phase shifts, subject to a set of minimum throughput requirements for individual devices. To address the resulting non-convex optimization problems, a successive convex approximation (SCA) based alternating optimization algorithm is proposed. Moreover, we study the case with the ideal linear EH model and two algorithms, namely SCA-based algorithm and semidefinite relaxation (SDR) algorithm, are proposed. Simulation results demonstrate the effectiveness of our proposed designs over various benchmark schemes and also unveil the importance of the joint design of IRS beamforming and PS rectifiers for achieving energy efficient WPCNs in practice. [ABSTRACT FROM AUTHOR]

In this paper an analytical model is introduced to describe the impulse response of the diffusive channel between a pointwise transmitter and a given fully-absorbing (FA) receiver in a molecular communication (MC) system. The presence of neighbouring FA nanomachines in the environment is taken into account by describing them as sources of negative molecules. The channel impulse responses of all the receivers are linked in a system of integral equations. The solution of the system with two receivers is obtained analytically. For a higher number of receivers the system of integral equations is solved numerically. It is also shown that the channel impulse response shape is distorted by the presence of the neighbouring FA interferers. For instance, there is a time shift of the peak in the number of absorbed molecules compared to the case without interference, as predicted by the proposed model. The analytical derivations are validated by means of particle based simulations. [ABSTRACT FROM AUTHOR]

In this paper, the legitimate surveillance of a suspicious mobile edge computing (MEC) network consisting of a suspicious edge server (SES) and multiple suspicious users (SUs), in the presence of a full-duplex monitor is studied. Each SU has a computation task to complete within a time deadline and can completely or partially offload the task to SES, while the monitor can either jam or assist the suspicious communications during task uploading and result downloading. With the heterogeneous offloading model adopted by the SUs, the problem of optimizing the monitor mode and transmit power to maximize the average ratio of successfully eavesdropped tasks, subject to the monitor transmit power constraint and the task completion time deadline constraint is investigated. The problem is solved via exploring the particular problem structure and adopting the sum-of-ratios optimization. Simulation results show that the proposed algorithm significantly outperforms the benchmark algorithms, especially for the SUs with partial offloading. It is also shown that the proposed algorithm is of low-complexity and achieves almost the same performance as the high-complexity optimal algorithm. Besides, compared to the SUs with binary offloading, the eavesdropping performance for the SUs with partial offloading is shown to be much better. [ABSTRACT FROM AUTHOR]

In the present paper a closed-form framework is derived for the analysis and optimization of the coverage probability (Pcov) and of the area spectral efficiency (ASE) in long-range (LoRa) networks. The proposed framework exploits stochastic geometry tools to associate the Pcov and the ASE to the end device (ED) transmit power and to the ED density. The analysis reveals the trends of the Pcov and of the ASE curves, with respect to both of the two parameters, while the robustness of the framework holds even at the asymptotic cases. Building upon the derived framework, the analysis demonstrates that no joint global optimum exists that jointly maximizes the Pcov over both parameters, suggesting that the optimization of the Pcov must be performed separately, for the two key network parameters considered. As opposed to that, the analysis demonstrates that a set of global optima exists that jointly maximize the ASE over both parameters, and these global maxima are subsequently derived in closed form. Thus, the derived framework fully characterizes the performance of LoRa networks, while defining in closed form the optimal points of operation that can be proven of significant value, for the transceiver and network design, of practical LoRa networks. [ABSTRACT FROM AUTHOR]

This paper develops a non-coherent index modulation (IM) system in which activation patterns are characterized by multi-level block codes. We analyze performance of such a system under the maximum-likelihood (ML) receiver and when the set of activation patterns follows a multi-level code generated from asymptotically optimal alphabets. An asymptotic analysis of the pair-wise error probability (PEP) shows that the system can exploit a diversity order that is determined by the distance of the worst codeword pair in the $l_{1}$ metric, known as the Manhattan norm. We then explore the rate-diversity tradeoff for the developed non-coherent IM system as a function of the code length. Specifically, Gilbert-style bounds on the data rates for systems based on binary and ternary codes are obtained that can ensure a given diversity order. We approach the problem of packing in the $l_{1}$ metric by partitioning codes into permutation modulation codes (PMCs) and obtaining Gilbert-style bounds on PMCs. Several achievable rates for non-coherent binary and ternary IM systems, as well as a tradeoff between the information rate and codeword error probability (CEP) are also derived. Finally, simulation results are provided to corroborate the theoretical analysis. [ABSTRACT FROM AUTHOR]

In this paper, fast fading Gaussian multiuser channels are considered. If the channel state information (CSI) is perfectly known to the transmitter, capacities have been derived for many cases in which the channels satisfy certain information-theoretic orders such as degradedness, or strong/very strong interference. We study the case when only the statistics of the CSI are known at the transmitter, which is an open problem in general. The main contributions of this paper are the following: First, we derive a sufficient condition to construct equivalent (having the same capacity region as the original channel) degraded Gaussian broadcast channels, which is based on the marginal distributions of the channel gains. To achieve this goal, we leverage three schemes: coupling, maximal coupling, and copulas, in addition to the same marginal property. The underlying idea of all schemes is to obtain an equivalent channel by changing the joint distribution in such a way that it satisfies a certain information-theoretic order while ensuring that the marginal distributions of the channels to different users are not changed. The construction of this equivalent multiuser channel allows us to directly apply existing capacity results. We then further derive the capacity regions of Gaussian interference channels with strong and very strong interferences, and also the secrecy capacity of Gaussian wiretap channels, while in all cases, the transmitters know only the statistics of the channels. Several practical examples such as Rayleigh fading and Nakagami- ${m}$ fading illustrate the applicability of the derived results. [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]

Many of the existing optimization-based transmit power control algorithms suffer from high computational complexity and require instantaneous global channel state information (CSI), both of which hinder their practical implementation. In this paper, we consider a wireless network with multiple transmitter-receiver pairs, where each transmitter only has access to its local CSI fed back from its intended receiver and does not require local CSI exchange with its neighboring transmitters. In such a network scenario, we propose a deep reinforcement learning based decentralized multi-agent power control (DEC-MAPC) algorithm for sum-rate maximization, where each transmitter acts as an intelligent agent. By leveraging the value decomposition technique, we establish a nonlinear mapping from the local reward of each agent to the global reward. Such a design allows each agent to independently control its transmit power based on its local CSI while enabling global collaboration among the agents. The proposed algorithm is scalable to large-scale networks as only local CSI is required, and is robust to the channel and interference variations via interacting with the environment. Simulation results show that the proposed DEC-MAPC algorithm with local CSI achieves comparable sum-rate performance with the centralized optimization algorithms with global CSI, while significantly reducing the computational complexity. [ABSTRACT FROM AUTHOR]

In this paper, we study the optimal resource allocation algorithm design for large intelligent reflecting surface (IRS)-assisted simultaneous wireless information and power transfer (SWIPT) systems. To facilitate efficient system design for large IRSs, instead of jointly optimizing all the IRS elements, we partition the IRS into several tiles and employ a scalable optimization framework comprising an offline design stage and an online optimization stage. In the offline stage, the IRS elements of each tile are jointly designed to support a set of different phase shift configurations, referred to as transmission modes, while the best transmission mode is selected from the set for each tile in the online stage. Given a transmission mode set, we aim to minimize the total base station (BS) transmit power by jointly optimizing the beamforming and the transmission mode selection policy taking into account the quality-of-service requirements of information decoding and non-linear energy harvesting receivers, respectively. Although the resource allocation algorithm design is formulated as a non-convex combinatorial optimization problem, we solve it optimally by applying the branch-and-bound (BnB) approach which entails a high computational complexity. To strike a balance between optimality and computational complexity, we also develop an efficient suboptimal algorithm capitalizing on the penalty method and successive convex approximation. Our simulation results show that the proposed designs enable considerable power savings compared to several baseline schemes. Moreover, our results reveal that by properly adjusting the numbers of tiles and transmission modes, the proposed scalable optimization framework indeed facilitates online design for large IRSs. Besides, our results confirm that the advocated physics-based model and scalable optimization framework enable a flexible trade-off between performance and complexity, which is vital for realizing the performance gains promised by large IRS-assisted communication systems in practice. [ABSTRACT FROM AUTHOR]

The integration of terrestrial and satellite communications (Satcom) is advocated for satisfying the challenging requirements of seamless, high-performance services. However, both the bandwidth and the power available are limited over satellite channels. In this paper, we propose index modulation (IM) and code-aided Satcom by conveying information by a pair of distinguishable constellation modes and their permutations. In order to combat both the linear and nonlinear distortion imposed by satellite channels, we conceive a factor graph (FG)-based iterative detection algorithm for Satcom relying on dual-mode (DM) IM (Sat-DMIM). The correlation amongst Sat-DMIM symbols imposed by both the channel-induced dispersion and the mode-selection mapping is explicitly represented by the FG constructed. Then the amalgamated belief propagation (BP) and mean field (MF) message passing algorithm is derived over this FG for detecting both the IM bits and the classic constellation mapping bits, while eliminating both the linear and nonlinear distortions. The complexity of the iterative detection algorithm is reduced by linearizing some high-order terms appearing in nonlinear distortion components using the a posteriori estimates of the Sat-DMIM symbols obtained from the previous iteration. Our simulation results demonstrate the power of the proposed amalgamated BP-MF-based and partial linearization approximation-based iterative detection algorithms. [ABSTRACT FROM AUTHOR]

Minimizing the symbol error in the uplink of multi-user multiple input multiple output systems is important, because the symbol error affects the achieved signal-to-interference-plus-noise ratio (SINR) and thereby the spectral efficiency of the system. Despite the vast literature available on minimum mean squared error (MMSE) receivers, previously proposed receivers for block fading channels do not minimize the symbol error in time-varying Rayleigh fading channels. Specifically, we show that the true MMSE receiver structure does not only depend on the statistics of the CSI error, but also on the autocorrelation coefficient of the time-variant channel. It turns out that calculating the average SINR when using the proposed receiver is highly non-trivial. In this paper, we employ a random matrix theoretical approach, which allows us to derive a quasi-closed form for the average SINR, which allows to obtain analytical exact results that give valuable insights into how the SINR depends on the number of antennas, employed pilot and data power and the covariance of the time-varying channel. We benchmark the performance of the proposed receiver against recently proposed receivers and find that the proposed MMSE receiver achieves higher SINR than the previously proposed ones, and this benefit increases with increasing autoregressive coefficient. [ABSTRACT FROM AUTHOR]

In this paper, we propose a symbol encryption method based on the complex-valued symbol multiplication and design the encryption symbol placement for offset quadrature amplitude modulation based filter bank multicarrier (OQAM/FBMC) systems. Specifically, we firstly analyze the encryption and decryption effects of complex-valued symbol multiplication on the original OQAM symbols. Then, by utilizing the intrinsic interference characteristics of prototype filters, a symbol encryption method and the placement design are proposed to simultaneously achieve the encryption of all OQAM symbols and low complexity decryption. Finally, the symbol error rate (SER), average signal transmit power, computational overhead and power spectral density (PSD) are analyzed. Simulation results are consistent with the theoretical analysis and demonstrate that the proposed method outperforms the traditional method based on imaginary-valued encryption symbol insertion in terms of the SERs of both legitimate and illegitimate receivers. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) are envisioned to be a disruptive wireless communication technique that is capable of reconfiguring the wireless propagation environment. In this paper, we study a free-space RIS-assisted multiple-input single-output (MISO) communication system in far-field operation. To maximize the received power from the physical and electromagnetic nature point of view, a comprehensive optimization, including beamforming of the transmitter, phase shifts of the RIS, orientation and position of the RIS is formulated and addressed. After exploiting the property of line-of-sight (LoS) links, we derive closed-form solutions of beamforming and phase shifts. For the non-trivial RIS position optimization problem in arbitrary three-dimensional space, a dimensional-reducing theory is proved. The simulation results show that the proposed closed-form beamforming and phase shifts approach the upper bound of the received power. The robustness of our proposed solutions in terms of the perturbation is also verified. Moreover, the RIS significantly enhances the performance of the mmWave/THz communication system. [ABSTRACT FROM AUTHOR]

In Internet of Things (IoT), the freshness of status updates is crucial for mission-critical applications. In this regard, it is suggested to quantify the freshness of updates by using Age of Information (AoI) from the receiver’s perspective. Specifically, the AoI measures the freshness over time. However, the freshness in the content is neglected. In this paper, we introduce an age-based utility, named as Age of Changed Information (AoCI), which captures both the passage of time and the change of information content. By modeling the underlying physical process as a discrete time Markov chain, we investigate the AoCI in a time-slotted status update system, where a sensor samples the physical process and transmits the update packets to the destination. With the aim of minimizing the weighted sum of the AoCI and the update cost, we formulate an infinite horizon average cost Markov Decision Process. We show that the optimal updating policy has a special structure with respect to the AoCI and identify the condition under which the special structure exists. By exploiting the special structure, we provide a low complexity relative policy iteration algorithm that finds the optimal updating policy. We further investigate the optimal policy for two special cases. In the first case where the state of the physical process transits with equiprobability, we show that optimal policy is of threshold type and derive the closed-form of the optimal threshold. We then study a more generalized periodic Markov model of the physical process in the second case. Lastly, simulation results are laid out to exhibit the performance of the optimal updating policy and its superiority over the zero-wait baseline policy. [ABSTRACT FROM AUTHOR]

Digital receivers based on 1-bit quantization and oversampling w.r.t. the transmit signal bandwidth promise lower energy consumption. However, since 1-bit quantization is a highly non-linear operation, standard off the shelf receiver algorithms cannot be applied. In this paper we consider an unknown phase rotation and timing offset and a fully digital receiver. To reduce the non-linear behavior introduced by 1-bit quantization, we assume that the receiver applies uniform phase and sample dithering, which can be implemented by sampling at an irrational normalized intermediate frequency and with an irrational oversampling factor, respectively. Based on the least squares objective function we derive a typical digital matched filter receiver with a data- and timing-aided phase estimator and square time recovery based timing estimation. Our main contribution is to show that both estimators are consistent under very general assumptions, e.g., arbitrary colored noise and stationary ergodic transmit symbols. Performance evaluations are done via simulations and are compared against a numerically computable upper bound of the Cramér–Rao lower bound. For low signal-to-noise ratio the estimators perform well but for high signal-to-noise ratio they run into an error floor. The performance loss of the phase estimator due to decision-directed operation or estimated timing information is marginal. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the statistics of the free space optics (FSO) communication channel between a hovering unmanned aerial vehicle (UAV) and a central unit. Two unique characteristics make UAV-based FSO systems significantly different from conventional FSO systems with static transceivers. First, for UAV-based FSO systems, the incident laser beam is not always orthogonal to the receiver lens plane. Second, both position and orientation of the UAV fluctuate over time due to dynamic wind load, inherent random air fluctuations in the atmosphere around the UAV, and internal vibrations of the UAV. On the contrary, for conventional FSO systems, the laser beam is always perpendicular to the receiver lens plane and the relative movement of the transceivers is limited. In this paper, we develop a novel channel model for UAV-based FSO systems by quantifying the corresponding geometric and misalignment losses (GML), while taking into account the non-orthogonality of the laser beam and the random fluctuations of the position and orientation of the UAV. In particular, for diverse weather conditions, we propose different fluctuation models for the position and orientation of the UAV and derive corresponding statistical models for the GML. We further analyze the performance of a UAV-based FSO link in terms of outage probability and ergodic rate and simplify the resulting analytical expressions for the high signal-to-noise ratio (SNR) regime. Finally, simulations validate the accuracy of the presented analysis and provide important insights for system design. For instance, we show that for a given variance of the fluctuations, the beam width should be properly adjusted to minimize the outage probability. [ABSTRACT FROM AUTHOR]