Search

In conventional multi-user multiple-input multiple-output (MU-MIMO) systems with frequency division duplexing (FDD), channel acquisition and precoder optimization processes have been designed separately although they are highly coupled. This paper studies an end-to-end design of downlink MU-MIMO systems which include pilot sequences, limited feedback, and precoding. To address this problem, we propose a novel deep learning (DL) framework which jointly optimizes the feedback information generation at users and the precoder design at a base station (BS). Each procedure in the MU-MIMO systems is replaced by intelligently designed multiple deep neural networks (DNN) units. At the BS, a neural network generates pilot sequences and helps the users obtain accurate channel state information. At each user, the channel feedback operation is carried out in a distributed manner by an individual user DNN. Then, another BS DNN collects feedback information from the users and determines the MIMO precoding matrices. A joint training algorithm is proposed to optimize all DNN units in an end-to-end manner. In addition, a training strategy which can avoid retraining for different network sizes for a scalable design is proposed. Numerical results demonstrate the effectiveness of the proposed DL framework compared to classical optimization techniques and other conventional DNN schemes. [ABSTRACT FROM AUTHOR]

The successive cancellation (SC) process in which symbols are decoded sequentially by processing some intermediate information is an essential component of various decoding algorithms used for polar codes and their variants. In some decoding schemes, we may need to redo this process from some specific symbol or from the first symbol. This operation is called rewinding. Rewinding the SC process seems trivial if we have access to all intermediate log-likelihood ratios (LLRs) and partial sums. However, as the block length increases, retaining all of the intermediate information becomes inefficient and impractical. Rewinding the SC process in a memory-efficient way is a problem that we address in this paper. As we store a fraction of all the intermediate information in the memory-efficient scheme, we may not be able to rewind the SC process to the target symbol index. The reason is that some of the stored intermediate information needed to decode the target symbol may have been overwritten. To recompute the lost information, we may need to rewind the process further. Before proposing the formal scheme for the rewinding process, we explore the known properties of the SC process based on the binary representation of the bit indices. Then, we introduce a new operator used for grouping the bit indices. This special grouping helps us in finding the closest bit index to the target index for rewinding. We also analytically prove that this approach gives access to the untouched intermediate information stored in the memory which is essential in resuming the SC process. Finally, we adapt the proposed approach to multiple rewinds and apply it to SC-flip decoding and shifted-pruning-based list decoding. The numerical evaluation of the proposed solution shows a significant reduction of ≥50% in the complexity of the additional decoding attempts at medium and high SNR regimes for SC-flip decoding and less for shifted-pruning based list decoding. [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]

The existing relay-assisted terahertz (THz) wireless system is limited to dual-hop transmission with pointing errors and short-term fading without considering the shadowing effect. This paper analyzes the performance of a multihop-assisted backhaul communication mixed with an access link under the shadowed fading with antenna misalignment errors. We derive novel probability density and distribution functions of the signal-to-noise ratio (SNR) of the multihop link employing channel-assisted (CA) and fixed-gain (FG) amplify-and-forward (AF) relaying for each hop by considering independent but not identically distributed (i.ni.d) $\alpha $ - $\mu $ fading channel with pointing errors. We present analytical expressions for the outage probability and average bit-error-rate (ABER) and develop asymptotic analysis in high SNR regime to derive the diversity order for both CA-multihop and FG-multihop backhaul links. We use the derived results of the multihop systems to analyze the statistical performance of the integrated backhaul-access relaying for both uplink and downlink transmission considering the generalized- $K$ shadowed fading model in the access link. We also present exact and asymptotic expressions of the outage probability for the considered mixed system. We perform computer simulations to provide design and deployment aspects of employing multiple relays to enhance THz wireless transmissions. [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 mmWave networks, a large or nearby object can obstruct multiple communication links, which results in spatial correlation in the blocking probability between a user and two or more base stations (BSs). This paper characterizes this blocking correlation and derives its impact on the signal-to-interference-plus-noise ratio (SINR) of a mmWave cellular network. We first present an exact analysis of a 1D network and highlight the impact of blocking correlation in the derived expressions. Gaining insights from the 1D analysis, we develop an analytical framework for a 2D network where we characterize the sum interference at the user by considering the correlation between the blocking of serving and interfering links. Using this, we derive the SINR coverage probability. Via simulations, we demonstrate that including blockage correlation in the analysis is required for accurate characterization of the system performance, in particular when the blocking objects tend to be large. [ABSTRACT FROM AUTHOR]

We consider performance enhancement of asymmetrically-clipped optical orthogonal frequency division multiplexing (ACO-OFDM) and related optical OFDM schemes, which are variations of OFDM in intensity-modulated optical wireless communications. Unlike most existing studies on specific designs of improved receivers, this paper investigates information theoretic limits of all possible receivers. For independent and identically distributed (IID) complex Gaussian inputs, we obtain an exact characterization of information rate of ACO-OFDM with improved receivers for all SNRs. It is proved that the high-SNR gain of improved receivers asymptotically achieve 1/4 bits per channel use, which is equivalent to 3 dB in electrical SNR or 1.5 dB in optical SNR; as the SNR decreases, the maximum achievable SNR gain of improved receivers decreases monotonically to a non-zero low-SNR limit, corresponding to an information rate gain of 36.3%. For practically used constellations, we derive an upper bound on the gain of improved receivers. Numerical results demonstrate that the upper bound can be approached to within 1 dB in optical SNR by combining existing improved receivers and coded modulation. We also show that our information theoretic analyses can be extended to Flip-OFDM and PAM-DMT. Our results imply that, for the considered schemes, improved receivers may reduce the gap to channel capacity significantly at low-to-moderate SNR. [ABSTRACT FROM AUTHOR]

In this paper, we consider an intelligent reflecting surface (IRS)-assisted cognitive radio system and maximize the secondary user (SU) rate by jointly optimizing the transmit power of secondary transmitter (ST) and the IRS’s reflect beamforming, subject to the constraints of the minimum required signal-to-interference-plus-noise ratio at the primary receiver, the ST’s maximum transmit power, and the unit modulus of the IRS reflect beamforming vector. This joint optimization problem can be solved suboptimally by the non-convex optimization techniques, which however usually require complicated mathematical transformations and are computationally intensive. To address this challenge, we propose an algorithm based on the deep deterministic policy gradient (DDPG) method. To achieve a higher learning efficiency and a lower reward variance, we propose another algorithm based on the soft actor-critic (SAC) method. In these proposed algorithms, a reward impact adjustment approach is proposed to improve their learning efficiency and stability. Simulation results show that the two proposed algorithms can achieve comparable SU rate performance with much shorter running time, as compared to the existing non-convex optimization-based benchmark algorithm, and that the proposed SAC-based algorithm learns faster and achieves a higher average reward with lower variance, as compared to the proposed DDPG-based algorithm. [ABSTRACT FROM AUTHOR]

Caching popular contents at edge networks (such as small-cell base stations) has been proposed to deal with the ever-growing mobile traffic. At the meantime, recommendation system is able to shape user demands for further prompting caching gain. In this paper, we study a multi-antenna multi-cell edge network employing transmit beamforming with caching-aware recommendation and user association. We first establish a framework for the joint problem of beamforming, user association, content caching and recommendation to minimize the content transmission delay of mobile users, by specifying a set of necessary conditions for all four component functions of the network. The resulting optimization problem corresponds to a non-convex, multi-timescale, and mixed-integer programming problem, which is hard to handle. To deal with the difficulty in solving the joint optimization problem by the direct formulation, we equivalently decompose it into three sub-problems. Then, we develop a computationally-efficient iterative algorithm to obtain the sub-optimal solution, where the three subproblems are tackled iteratively. Simulation results are conducted to demonstrate that the proposed algorithm can obtain lower transmission delay than baseline schemes. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is an emerging cost-efficient technology to enhance communication performance by implementing a large number of passive reflecting elements with tunable phases in wireless systems. In this paper, we propose a general framework for the IRS-aided MIMO system designs under both single-user and multi-user setups, in which the diverse performance metrics including weighted mutual information and weighted MSE, and the realistic multiple weighted power constraint are taken into consideration. Leveraging the alternating optimization approach, the optimal IRS phase shifts are obtained in semi-closed forms. Specifically, based on the matrix-monotonic optimization theory, it is found that optimizing IRS phase shifts is essentially equivalent to tuning the eigenvalues and the corresponding eigenvectors of the MSE matrix. Then the proposed general framework is extended to a multi-user system by introducing a majorization-minimization (MM)-based method for IRS phase shift optimization. Simulation results show that our proposed optimal design brings significant enhancement on the chosen performance metric compared to the traditional MIMO systems without the IRS, and also significantly outperforms various benchmark designs in both single-user and multi-user systems. [ABSTRACT FROM AUTHOR]

This paper considers the finite-order filter design problem for the source and multiple full-duplex (FD) relays in a cooperative communication system under frequency-selective fading channels. The goal is to optimize the source and relay filters such that the end-to-end signal-to-interference-plus-noise ratio (SINR) of minimum mean-squared error decision-feedback equalizer (MMSE-DFE) can be maximized. The resultant design problem is very difficult since we need to deal with self interference (SI), inter-relay interference (IRI), and inter-symbol interference (ISI) at the same time. Novel designs are then proposed to overcome the difficulty in this work. Transforming the signals into the frequency domain and using some optimization techniques, we first theoretically derive the power spectrum of the source filter and the spectrums of the relay filters. Then, the finite-order design is developed to approach the derived spectrums. Based on the weighted least-square (WLS) criterion, the Steiglitz-McBride method is exploited to obtain the filter coefficients in finite lengths. Numerical results demonstrated that complete removal of SI may not be a good strategy; preserving a certain amount of SI at each relay instead provides better SINR performance. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV)-enabled communications have been proposed as a critical part of the beyond fifth-generation (5G) cellular networks. This type of communications is frequently characterized by line-of-sight (LoS) and dynamic propagation conditions. However, in various scenarios, the presence of large obstacles in the LoS path is unavoidable, resulting in shadowed fading environments. In this paper, a new channel model is proposed, in which the effects of mobility and shadowing are simultaneously considered. In particular, the performance of a UAV-based communication system operating in a shadowed double-scattering channel is analyzed. The new channel model is generic, since it models various fading/shadowing conditions, while it is in terms of easy-to-evaluate mathematical functions. Moreover, a low complexity UAV selection policy is proposed, which exploits shadowing-related information. The proposed scheme offers a reduction of the signal processing complexity, without any important degradation on the performance, as compared to alternatives approaches. In this context, a new analytical framework has been developed for investigating the performance of the new strategy. Finally, the main outcomes of this paper are also validated by empirical data, collected in an air-to-ground measurement campaign. [ABSTRACT FROM AUTHOR]

This paper investigates the channel capacity of coherent reception with antenna diversity in Rayleigh fading using asymmetric constellations, such as nonbinary two-sided amplitude-shift keying (ASK) and quadrature amplitude modulation (QAM) with ≥ 8 levels. Due to the asymmetries, the capacity achieving input or a priori probability distributions deviate from uniformity. To perform the investigation, an analytical expression for the mutual information, in terms of an integral over a single variable, between the input (transmitted symbol) and the output (received signal vector comprising signals at receive antennas), is derived. For two-sided ASK, 8-QAM with cross constellation, and 16-QAM, analytical closed form expressions for the high and low signal-to-noise (SNR) approximations, respectively, of the capacity achieving input probability distribution, the capacity, and the relative gain in mutual information (between using the uniform and the capacity achieving input probability distributions) are obtained. Numerical results show that at low SNRs, the use of the capacity achieving nonuniform input probability distribution offers significant advantage over the use of the uniform input probability distribution, while at high SNRs, this advantage is significant only for configurations with one receive antenna. Furthermore, the high and low SNR approximations are shown to be reasonably accurate. [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]

In this paper, we investigate the performance of an RIS-aided wireless communication system subject to outdated channel state information that may operate in both the near- and far-field regions. In particular, we take two RIS deployment strategies into consideration: (i) the centralized deployment, where all the reflecting elements are installed on a single RIS and (ii) the distributed deployment, where the same number of reflecting elements are placed on multiple RISs. For both deployment strategies, we derive accurate closed-form approximations for the ergodic capacity, and we introduce tight upper and lower bounds for the ergodic capacity to obtain useful design insights. From this analysis, we unveil that an increase of the transmit power, the Rician- $K$ factor, the accuracy of the channel state information and the number of reflecting elements help improve the system performance. Moreover, we prove that the centralized RIS-aided deployment may achieve a higher ergodic capacity as compared with the distributed RIS-aided deployment when the RIS is located near the base station or near the user. In different setups, on the other hand, we prove that the distributed deployment outperforms the centralized deployment. Finally, the analytical results are verified by using Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In this paper, we study joint adaptive M-QAM modulation and power adaptation for a downlink two-user non-orthogonal multiple access (NOMA) network. Without sacrificing bit error rate (BER), joint adaptive transmission can fully utilize the time-varying nature of wireless channels, by allowing both power and rate to adapt to channel fading. Two adaptive power allocation strategies, namely, Scheme 1 and Scheme 2, each of which guarantees the minimum target rate for one user while supporting the highest possible rate for the other, are first proposed. Then, based on the two power schemes, the performance of joint adaptive transmission in terms of average spectral efficiency (SE) is studied for continuous-rate and discrete-rate modulation, while guaranteeing the minimum required rate and BER requirements. With the focus on practical discrete-rate M-QAM modulation, it is proved that for the strong user in Scheme 1 and the weak user in Scheme 2, their average SEs converge to the minimum target rates. In order to further increase the total transmission rate, we then propose a dynamic rate and power adaptation (DRPA) algorithm, aiming to increase the rate of one user without sacrificing the rate of the other. It is shown that at high SNRs, the DRPA algorithm allows the strong user in Scheme 1 and the weak user in Scheme 2 to continue to increase their transmission rates until reaching the highest modulation order that the system can support. Hence, the total transmission rate can be greatly increased at high SNRs due to the adoption of DRPA, by allowing both users in each scheme to reach the highest transmission rate in the system. [ABSTRACT FROM AUTHOR]

It is challenging to quantify the left tail behavior of the cumulative distribution function of a sum of lognormal random variables, especially when they are correlated and non-identically distributed. The mathematical intractability hampers the analysis on diversity receptions over lognormal fading channels. In this paper, a novel asymptotic technique is exploited to study non-identically distributed dual-branch lognormal fading channels with correlation. Closed-form asymptotic outage probability expressions are derived for maximum-ratio combining (MRC), equal-gain combining (EGC), and selection combining (SC). Three counterintuitive facts are revealed: 1) one of the two channels contributes no asymptotic performance gain to the diversity reception systems under certain conditions, implying that a link can be discarded without causing asymptotic performance loss; 2) SC outperforms EGC under certain conditions; and 3) the outage probability of SC is arbitrarily close to that of MRC under certain conditions. The new result reveals insights into the long-standing problem of asymptotic analysis for correlated lognormal fading channels, paving the way for analysis on more general channel models. This paper also provides an efficient approach to evaluate the non-identically distributed lognormal fading channels at a high signal-to-noise ratio. Practically, the analytical results prevent some redundant units that contribute no performance gain. [ABSTRACT FROM AUTHOR]

Ultra-Reliable and Low-Latency Communications (URLLC) has attracted considerable attention because of its potential applications in factory automation, automated driving, and telesurgery anticipated for the era of the sixth-Generation (6G) networks. In URLLC with random channel gains and a hard delay constraint, the scheduling of backlogged queues and finite blocklength coding in the physical layer will make it very challenging to specify its performance limits. In this paper, we focus our attention on the asymptotic cross-layer analysis of URLLC when the Signal-to-Noise Ratio (SNR) is sufficiently high. More specifically, we find that a fundamental tradeoff exists among the service capability, latency, and error probability in the high SNR regime, which is characterized by a gain conservation equation. The main result of this work reveals that the sum of our defined service rate gain, real-time gain, and reliability gain is equal to one under the optimal policy. Numerical simulations are also exploited to validate that the derived gain conservation equation holds even with bounded random arrival. [ABSTRACT FROM AUTHOR]

This paper formulates the polar-code construction problem for the successive-cancellation list (SCL) decoder as a maze-traversing game, which can be solved by reinforcement-learning techniques. The proposed method provides a novel technique for polar-code construction that no longer depends on sorting and selecting bit-channels by reliability, as in most current algorithms. Instead, this technique decides whether the input bits should be frozen in a purely sequential manner. The equivalence of optimizing the polar-code construction for the SCL decoder under this technique and maximizing the expected reward of traversing a maze is drawn. Simulation results show that the standard polar-code constructions that are designed for the successive-cancellation decoder are no longer optimal for the SCL decoder with respect to the frame error rate (FER). In contrast, the proposed game-based construction method finds code constructions that have similar or lower FER for various code lengths and various list sizes of the SCL decoder, compared to the state-of-the-art construction methods. The advantage of the game-based constructions over the standard constructions increases with the channel signal-to-noise ratio and the list size of SCL decoding. Moreover, the learning is highly efficient in terms of the number of required training samples and computational operations. [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 study the statistical characterization and modeling of distributed multi-reconfigurable intelligent surface (RIS)-aided wireless systems. Specifically, we consider a practical system model where the RISs with different geometric sizes are distributively deployed, and wireless channels associated to different RISs are assumed to be independent but not identically distributed (i.n.i.d.). We propose two purpose-oriented multi-RIS-aided schemes, namely, the exhaustive RIS-aided (ERA) and opportunistic RIS-aided (ORA) schemes. A mathematical framework, which relies on the method of moments, is proposed to statistically characterize the end-to-end (e2e) channels of these schemes. It is shown that either a Gamma distribution or a Log-Normal distribution can be used to approximate the distribution of the magnitude of the e2e channel coefficients in both schemes. With these findings, we evaluate the performance of the two schemes in terms of outage probability (OP) and ergodic capacity (EC), where tight approximate closed-form expressions for the OP and EC are derived. Representative results show that the ERA scheme outperforms the ORA scheme in terms of OP and EC. In addition, under i.n.i.d. fading channels, the reflecting element settings and location settings of RISs have a significant impact on the system performance of both the ERA or ORA schemes. [ABSTRACT FROM AUTHOR]

Operating beyond-5G networks at the millimeter wave (mmWave) band imposes technological challenges while offering great opportunities. The nature of millimeter waves renders the communication quality susceptible due to blockage caused by obstacles. Hence, multi-hop relaying is likely to play a significant role in improving the performance of mmWave networks. In this paper, we investigate the performance of two appropriate routing techniques for mmWave networks, namely minimum hop count (MHC) and nearest LoS relay to the destination with MHC (NLR-MHC). Analytical models are provided to evaluate the performance of the two routing techniques using tools from stochastic geometry. We model the distribution of hop count using phase-type distribution, and then we use this distribution to derive analytical results for the coverage probability and spectral efficiency. Results reveal the significant impact of densities of relays and blockages on the performance of the aforementioned routing techniques in-terms of spectral efficiency, connectivity probability, and average hop count. It is also demonstrated that NLR-MHC achieves a superior coverage probability and spectral efficiency compared to MHC. However, MHC provides better performance in-terms of connectivity probability and average hop count. [ABSTRACT FROM AUTHOR]

Channel estimation is challenging for the reconfigurable intelligent surface (RIS)-aided wireless communications. Since the number of coefficients of the cascaded channel among the base station (BS), the RIS, and the user equipment (UE), is the product of the number of BS antennas, the number of RIS elements, and the number of UEs, the pilot overhead can be prohibitively high. In this paper, we propose a two-timescale channel estimation framework to exploit the property that the BS-RIS channel is high-dimensional but quasi-static, while the RIS-UE channel is mobile but low-dimensional. Specifically, to estimate the quasi-static BS-RIS channel, we propose a dual-link pilot transmission scheme, where the BS transmits downlink pilots and receives uplink pilots reflected by the RIS. Then, we propose a coordinate descent-based algorithm to recover the BS-RIS channel. Since the quasi-static BS-RIS channel is estimated less frequently than the mobile channel is, the average pilot overhead can be reduced from a long-term perspective. Although the mobile RIS-UE channel has to be frequently estimated in a small timescale, the associated pilot overhead is low thanks to its low dimension. Simulation results show that the proposed two-timescale channel estimation framework can achieve accurate channel estimation with low pilot overhead. [ABSTRACT FROM AUTHOR]

Hardware impairment is inevitable in many wireless systems. It is particularly severe in low-cost applications due to the imperfect components used. In this paper, the channel estimation and non-coherent detection problems of hardware impaired signals are studied for a single-carrier, single-antenna and single-hop system. Specifically, three different cases are investigated: signals with additive distortion only, signals with in-phase and quadrature imbalance only, and signals with both impairments. The maximum likelihood and Gaussian approximation methods are used to derive the new non-coherent detectors for amplitude modulated signals, while the maximum likelihood and moment-based methods are employed to design the new channel estimators for all signals. Numerical results show that the new non-coherent detectors outperform the existing non-coherent detectors in the presence of hardware impairment. The performance gain can be as high as 8 dB. They also show that the new channel estimators have much higher accuracy than the existing estimator. In some conditions, the accuracy of the new estimator is about 100 times that of the existing estimator. [ABSTRACT FROM AUTHOR]

This paper proposes a new finite precision iterative decoder for low-density parity-check (LDPC) codes. The proposed decoder, named Sign-Preserving Min-Sum (SP-MS), significantly improves the decoding performance compared to the classical Offset Min-Sum (OMS) decoder when messages are quantized on $q=2$ , 3, or 4 bits. The particularity of the SP-MS decoder is that messages cannot take the 0 value, and can fully benefit from the $q$ bits of precision. The optimization of the SP-MS decoder is investigated in the asymptotic limit of the code length using density evolution (DE). Our study shows that 3-bit SP-MS decoders can achieve the same error-correcting performance as 5-bit OMS decoders, and 2-bit SP-MS decoders outperform 3-bit OMS decoders. The finite-length simulations confirm the conclusions of the DE analysis for several LDPC codes. Our SP-MS decoder shows a signal-to-noise ratio (SNR) gain up to 0.43 dB, with a memory/wire reduction of up to 40%, compared to the OMS decoder. Moreover, the SP-MS decoder converges faster and uses fewer iterations than the OMS decoder, with an improvement of up to 83.3% of the average decoding throughput. On an FPGA, the SP-MS decoder reduces resource utilization by up to 56% compared to the OMS decoder. [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 consider a multi-user multiple-input multiple-output (MIMO) system aided by multiple intelligent reflecting surfaces (IRSs) that are deployed to increase the coverage and, possibly, the rank of the channel. We propose an optimization algorithm to configure the IRSs, which is aimed at maximizing the network sum-rate by exploiting only the statistical characterization of the locations of the mobile users. As a consequence, the proposed approach does not require the estimation of either instantaneous channel state information (CSI) or second-order channel statistics for IRS optimization, thus significantly relaxing (or even avoiding) the need of frequently reconfiguring the IRSs, which constitutes one of the most critical issues in IRS-assisted systems. Numerical results confirm the validity of the proposed approach. It is shown, in particular, that IRS-assisted wireless systems that are optimized based on statistical position information still provide large performance gains as compared to the baseline scenarios in which no IRSs are deployed. [ABSTRACT FROM AUTHOR]

This paper provides a deep analysis for millimeter-wave device-to-device (mm-wave D2D) underlaid cellular networks to investigate how the performance of individual users or link percentiles under constraints are affected by the interaction between D2D and cellular communication modes integrated with the salient mm-wave features. Under a general Nakagami fading model, we derive the upper bounds for the $b$ -moments of the conditional signal-to-interference-noise ratio (SINR) distributions for the two modes given the network realization, and further calculate the upper bounds of SINR meta distributions (MDs). Moreover, we extend the MD-based analysis to evaluate the fine-grained performance for the transmission effectiveness, through deriving the bounding results for the user-perceived rate MD and spatial rate capacity (SRC), the latter of which is defined as the effective density of users satisfying a given transmission rate requirement with a certain probability. Numerical results validate the tightness of the proposed bounds and reveal the different effects of the network configuration parameter associated with mm-wave on the link and network performances from the view of individual users. [ABSTRACT FROM AUTHOR]

This paper considers the application of widely linear (WL) receivers in an uplink multi-user system using real-valued modulation schemes, where the cellular base station (BS) with multiple antennas provides connectivity for randomly deployed single-antenna users. The targeted use case is massive machine type communication (mMTC) with grant-free access in the uplink, where the network is required to host a large number of low data rate devices transmitting in an uncoordinated fashion. Four types of WL receivers are investigated, namely the WL zero-forcing (ZF) and the WL minimum mean-squared error (MMSE) receivers, along with their enhanced versions employing successive interference cancellation (SIC) with channel-dependent ordering, i.e., the WL-ZF-SIC and WL-MMSE-SIC receivers. The outage performances of these receivers are analytically characterized in the high signal-to-noise ratio (SNR) regime and compared to those of conventional linear (CL) receivers using complex-valued modulation schemes. For the non-SIC receivers, we show that, when compared to the CL counterparts, the WL receivers yield a higher diversity gain when decoding the same number of users and have the same diversity gain but a decreased coding gain when the number of users is nearly doubled. The outage performance analysis of WL-SIC receivers is facilitated by the marginal distribution of ordered eigenvalues of a real-valued Wishart matrix. It is shown that the SIC operation with channel-dependent ordering brings no additional diversity gain to the WL receivers but instead increases the coding gain. Moreover, the coding gain of WL-SIC receivers grows as the number of users increases and even exceeds that of CL-SIC receivers under suitable conditions. For the mMTC scenario with grant-free transmission, it is demonstrated that the WL receivers outperform their CL counterparts in terms of offering a lower outage (and packet drop) probability and a higher system throughput for a given packet drop probability. [ABSTRACT FROM AUTHOR]

The problem of coding for informed receivers (IR) is considered, where a transmitter multicasts a bunch of messages to its associated receivers, each of which already has a subset of messages as side information. Which receiver has what side information is unknown to the transmitter. A family of polar codes for IR was proposed for binary-input channels in (Huang and Shieh, 2018), which was shown to provide excellent side information gain regardless of side information configuration and content. A trial extension of this scheme to high-order modulations, however, was unsatisfactory. In this paper, two families of systematic polar coded modulations for IR are proposed. In the first family, by building a connection between the message bits and modulated symbols under systematic polar codes, we leverage the bit assignments and labeling techniques such that receiver side information can be directly translated to a minimum distance gain. In the second family, a permutation operation is added before modulation such that the message bits can be properly reordered to further advance and balance the gains among different side information configurations. Simulations show that the proposed schemes provide large and balanced side information gains and significantly outperform the system directly adapted from (Huang and Shieh, 2018) onto high-order modulations. [ABSTRACT FROM AUTHOR]

In order to satisfy the requirement of extremely high data rate in traffic hotspot regions, millimeter wave (mmWave) has attracted significant attention in wireless communication networks. While the coverage performance of mmWave networks based on the distribution of signal-to-interference-plus-noise ratio (SINR) has been widely studied, it provides only very limited information on the link reliability. In this paper, we provide a fine-grained performance analysis of the mmWave networks with hotspots. Specifically, we first establish a general and tractable framework to investigate the performance of mmWave networks using the Poisson cluster process integrated with several features of the mmWave band. Both open and closed association strategies are considered. To show what fraction of users in the networks achieves target reliability when the SINR is given, we derive the tier association probability and the moments of the conditional SINR distribution, based on which the exact meta distributions of SINR are given. Interestingly, in clustered mmWave networks, the widely used standard and generalized beta approximations do not work well when the blockage effect is severe. To resolve this issue, we provide a modified approximation by scaling the standard beta distribution, which is shown to be closer to the exact results. We conduct extensive simulations to study the impact of mmWave and deployment features on the performance of clustered mmWave networks. Numerical results reveal that the optimal scattering variance of mmWave base stations scales with the cluster size to maximize the number of concurrent reliable links, and increasing the antenna directivity results in more reliable communications than elevating the transmit power of mmWave base stations. [ABSTRACT FROM AUTHOR]

To achieve better connectivity in future communication networks, the deployment of different types of access points (APs) is underway. APs are expected to be equipped with self-organizing capabilities to reduce costs. Moreover, due to the spectrum crunch, frequency reuse among the deployed APs is inevitable, exacerbating the problem of inter-cell interference (ICI). Therefore, ICI mitigation in self-organizing networks (SONs) is commonly identified as a key radio resource management mechanism to enhance performance. To this end, this paper proposes a novel solution for the uncoordinated channel and power allocation problems. Based on the multi-armed bandits (MAB) framework, the proposed technique does not require any communication between the APs. The case of varying channel rewards across APs is considered. In contrast to previous work on channel allocation using the MAB framework, APs are permitted to choose multiple channels for transmission. Moreover, non-orthogonal multiple access is used, allowing multiple APs to access each channel simultaneously. This results in an MAB model with varying channel rewards, multiple plays and non-zero reward on collision. The proposed algorithm has an expected regret in the order of $\mathcal {O}(\log ^{2}T)$ , with extensive numerical results revealing it significantly outperforms a well-known baseline algorithm in terms of energy efficiency. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is deemed as a promising solution to improve the spectral and energy efficiency of wireless communications cost-effectively. In this paper, we consider a wireless network where multiple base stations (BSs) serve their respective users with the aid of distributed IRSs in the downlink communication. Specifically, each IRS assists in the transmission from its associated BS to user via passive beamforming, while in the meantime, it also randomly scatters the signals from other co-channel BSs, thus resulting in additional signal as well as interference paths in the network. As such, a new IRS-user/BS association problem arises pertaining to optimally balance the passive beamforming gains from all IRSs among different BS-user communication links. To address this new problem, we first derive a tractable lower bound of the average signal-to-interference-plus-noise ratio (SINR) at the receiver of each user, termed average-signal-to-average-interference-plus-noise ratio (ASAINR), based on which two ASAINR balancing problems are formulated to maximize the minimum ASAINR among all users by optimizing the IRS-user associations without and with BS transmit power control, respectively. We also characterize the scaling behavior of user ASAINRs with the increasing number of IRS reflecting elements to investigate the different effects of IRS-reflected signal versus interference power. Moreover, to solve the two ASAINR balancing problems that are both non-convex optimization problems, we propose an optimal solution to the problem without BS power control and low-complexity suboptimal solutions to both problems by applying the branch-and-bound method and exploiting new properties of the IRS-user associations, respectively. Numerical results verify our performance analysis and also demonstrate significant performance gains of the proposed solutions over benchmark schemes. [ABSTRACT FROM AUTHOR]

In this paper, we conduct rate-distortion and outage probability analyses for Wyner-Ziv (WZ) systems, where the information sequences from a source and a helper are transmitted to the destination over block Rayleigh fading multiple access channels (MACs). This work has been motivated by decision-making systems, where the aim is to make right decisions based on the observations. Hence, the most critical performance metric is the accuracy of decisions, even allowing distortion in wireless transmission. A sufficient condition for the successful transmissions is that the WZ and MAC regions intersect. For the ease of calculating the outage probability, we propose an approximated, yet accurate, WZ rate region. The outage probabilities of the WZ systems are then evaluated both in orthogonal and MAC transmissions. It is shown that the transmission efficiency of the system with MAC is significantly improved compared to orthogonal transmission. Furthermore, a helper-selection scheme is introduced to further reduce the outage probability of the WZ-MAC systems. The results show that the outage probability decreases, of which decay corresponds to the $(L+1)$ -order diversity with $L$ helpers in small value range of the average signal-to-noise ratio (SNR), while it converges into $L$ as the average SNR becomes large. [ABSTRACT FROM AUTHOR]

Slotted Aloha provides a simple way for accommodating the massive access of Machine-to-Machine (M2M) communications. Yet, the delay performance of slotted Aloha has long been observed to significantly deteriorate as the network size grows. It is therefore important to study how to optimize the delay performance of slotted Aloha in a large-scale network. This paper focuses on the optimization of access delay of a buffered slotted Aloha network, where $n$ nodes transmit to a common receiver in fading channels. Specifically, by deriving the closed-form expressions of the network steady-state points in both unsaturated and saturated conditions, the first and second moments of access delay of each packet are obtained as explicit functions of system parameters, and minimized by optimizing the transmission probability of each node. The analysis shows that to achieve the minimum mean access delay, the transmission probability of each node should be reduced as the network size increases, leading to a diminishing node data rate unless the information encoding rate is jointly optimized. The minimum mean access delay for a given data rate requirement is further characterized, and effects of key parameters such as the minimum required data rate for each node, the mean received signal-to-noise ratio of each packet and the number of nodes on the rate-constrained minimum mean access delay are discussed. The practical insights of the analysis are also demonstrated by taking the example of an LTE-M system with smart grid applications. [ABSTRACT FROM AUTHOR]

This paper proposes unprecedented Expectation Propagation (EP)-based receivers for Circular Faster-Than-Nyquist (CFTN) signaling. This concept yields a Minimum Mean-Square-Error equalizer for InterSymbol Interference (ISI) processing combined with a block which we call Constellation Matcher in charge of the symbol estimates realignment with the constellation. From this framework, we explore different scheduling strategies leading to iterative EP-based receivers with our without decision feedback. Then, by extending the family of the EP process to a subset of non-circular Gaussian distributions results in a Widely Linear (WL) equalization. This new WL-EP receiver best fits the CFTN model, allowing enhanced performance at the cost of a slightly increased complexity. Also, we propose to restrict the Gaussian family to circular Gaussian distributions with identity covariance matrices up to a scaling factor. Combined with CFTN, this particular family allows a low-complexity Frequency-Domain processing of the equalization without requiring any cyclic prefix. The proposed EP-based receivers for CFTN are then evaluated for different spectral efficiencies and computational complexities. Our simulations show that they completely handle the ISI up to 5 bits/s/Hz and double the spectral efficiency compared to Nyquist signaling with almost no performance loss. [ABSTRACT FROM AUTHOR]

In this paper, we consider non-coherent detection schemes for molecular communication systems in the presence of inter-symbol-interference. In particular, we study non-coherent detectors based on memory-bits-based thresholds in order to achieve low bit-error-ratio (BER) transmission. The main challenge of realizing detectors based on memory-bits-based thresholds is to obtain the channel state information based only on the received signals. We tackle this issue by reformulating the thresholds through intermediate variables, which can be obtained by clustering multi-dimensional data from the received signals, and by using the K-means clustering algorithm. In addition to estimating the thresholds, we show that the transmitted bits can be retrieved from the clustered data. To reduce clustering errors, we propose iterative clustering methods from one-dimensional to multi-dimensional data, which are shown to reduce the BER. Simulation results are presented to verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, by considering the average mean squared error (AMSE) of channel estimation, we primarily obtain the closed-from expressions of the probability density function (PDF) and cumulative distribution function of AMSE for the least squares (LS)/minimum mean squared error (MMSE) estimation method as the line-of-sight (LOS) component is known, where the asymptotic analysis is executed in Rayleigh fading and strong LOS conditions. Secondly, the closed-form expressions for the expectation of AMSE (Expamse) and variance of AMSE (Varamse) are acquired, where Varamse is inversely proportional to the number of antennas (M). As M becomes infinite, the PDF of AMSE at Expamse has an order of root M. When the pilot power decreases with M in a power law, the LS case keeps deteriorating while the MMSE case converges to a constant which basically depends on the Rician K-factor. Next, the spectral efficiency is investigated by considering AMSE. When Expamse accelerates, the spectral efficiency of the LS method keeps dropping and that of the MMSE method firstly is degraded and then is improved to a constant except Rayleigh fading. Finally, all results are validated via simulations. [ABSTRACT FROM AUTHOR]

This paper derives the distribution of the maximum end-to-end (e2e) signal to noise ratio (SNR) in an opportunistic relay selection based cooperative relaying network having a large number of non-identical relay links. The source is simultaneous wireless information and power transfer enabled, and the relays are capable of both time splitting (TS) and power splitting (PS) based energy harvesting (EH). Contrary to the majority of literature in communication, which uses extreme value theory (EVT) to derive the statistics of extremes of sequences of independent and identically distributed random variables (RVs), we demonstrate how EVT can be used to derive the maximum statistics of sequences of independent and non-identically distributed normalised SNR and hence the distribution of the maximum SNR. Using these results, we derive simple expressions for evaluating the outage capacity, and achievable throughput at the destination. Finally, we present the utility of the results for deciding the optimum TS and PS factors of the hybrid EH relays that maximise outage capacity, and achievable throughput at the destination. Furthermore, we establish the stochastic ordering of the e2e SNR, which in turn allows the characterisation of the variations in the e2e performance with respect to the variations in different system parameters. [ABSTRACT FROM AUTHOR]

In the near future, it is envisioned that cellular networks will have to cope with extensive internet of things (IoT) devices. Therefore, a required feature of cellular IoT will be the capability to serve simultaneously a large number of devices with heterogeneous demands and qualities of channel state information at the transmitter (CSIT). In this paper, we focus on an overloaded multiple-input single-output (MISO) broadcast channel (BC) with two groups of CSIT qualities, namely, one group of users (representative of high-end devices) for which the transmitter has partial knowledge of the CSI, the other group of users (representative of IoT devices) for which the transmitter only has knowledge of the statistical CSI (i.e., the distribution information of the user channels). We introduce rate-splitting multiple access (RSMA), a new multiple access based on multi-antenna rate-splitting (RS) technique for cellular IoT. Two strategies are proposed, namely, time partitioning–RSMA (TP–RSMA) and power partitioning–RSMA (PP–RSMA). The former independently serves the two groups of users over orthogonal time slots while the latter jointly serves the two groups of users within the same time slot in a non-orthogonal manner. We first show at high signal-to-noise ratio (SNR) that PP–RSMA achieves the optimal degrees-of-freedom (DoF) in an overloaded MISO BC with heterogeneous CSIT qualities. We then show at finite SNR that PP–RSMA achieves explicit sum rate gain over TP–RSMA and all baseline schemes by marrying the benefits of PP and RSMA. Furthermore, PP–RSMA is robust to CSIT inaccuracy and flexible to cope with quality of service (QoS) rate constraints of all users. The DoF and rate analysis helps us in drawing the conclusion that PP–RSMA is a powerful framework for cellular IoT with a large number of devices. [ABSTRACT FROM AUTHOR]

In this paper, we develop an innovative approach to quantitatively characterize the performance of ultra-dense wireless networks in a plethora of propagation environments. The proposed framework has the potential of simplifying the cumbersome procedure of analyzing the coverage probability and allowing the unification of single- and multi-antenna networks through compact analytical representations. By harnessing this key feature, we develop a novel statistical machinery to study the scaling laws of wireless networks densification considering general channel power distributions including small-scale fading and shadowing as well as associated beamforming and array gains due to the use of multiple antenna. We further formulate the relationship between network density, antenna height, antenna array seize and carrier frequency showing how the coverage probability can be maintained with ultra-densification. From a system design perspective, we show that, if multiple antenna base stations are deployed at higher frequencies, monotonically increasing the coverage probability by means of ultra-densification is possible, and this without lowering the antenna height. Simulation results substantiate performance trends leveraging network densification and antenna deployment and configuration against path loss models and signal-to-noise plus interference thresholds. [ABSTRACT FROM AUTHOR]

Alternating direction method of multipliers (ADMM) is an efficient implementation of linear programming (LP) decoding for low-density parity-check (LDPC) codes. By adding penalty terms to the objective function of the LP decoding model, ADMM variable node (VN) penalized decoding can suppress the non-integral solutions and improve the frame error rate (FER) performance in the low signal-to-noise ratio (SNR) region. In this paper, we propose a novel ADMM check node (CN) penalized decoding algorithm. Codeword solutions which satisfy all parity-check equations will have smaller penalty values than non-codeword solutions, including the non-integral solutions. We discuss the required properties of CN-penalty functions, propose a few functions that satisfy those properties, and study their performance/complexity trade-offs. We also investigate the convergence properties of the proposed algorithm and prove that its performance is independent of the transmitted codeword. Using Monte Carlo simulations and instanton analysis, we then demonstrate that the proposed CN-penalized decoder outperforms ADMM VN penalized decoders in both waterfall and error floor regions. This comes at the expense of some increase in the decoding complexity. [ABSTRACT FROM AUTHOR]

This paper investigates the design and performance of delayed bit-interleaved coded modulation (DBICM) with low-density parity-check (LDPC) codes. For Gray labeled square M-ary quadrature amplitude modulation (QAM) constellations, we investigate the optimal delay scheme with the largest spectrum efficiency of DBICM for a fixed maximum number of delayed time slots and a given signal-to-noise ratio. When analyzing the capacity of DBICM, we find two important properties: the capacity improvement due to delayed coded bits being mapped to the real and imaginary parts of the transmitted symbols are independent of each other; a pair of delay schemes with delayed coded bits having identical bit-channel capacity lead to equivalent DBICM capacity. Using these two properties, we efficiently optimize the delay scheme for any uniform Gray-QAM systems. Furthermore, these two properties enable efficient LDPC code designs regarding unequal error protection via bit-channel type classifications. Moreover, we use protograph-based extrinsic information transfer charts to jointly optimize degree distributions and channel assignments of LDPC codes and propose a constrained progressive edge growth like algorithm to jointly construct LDPC codes and bit-interleavers for DBICM, taking distinctive bit-channel’s capacity into account. Simulation results demonstrate that the designed LDPC coded DBICM systems significantly outperform LDPC coded BICM systems. [ABSTRACT FROM AUTHOR]

We consider the problem of joint channel estimation and data decoding in uplink massive multiple input multiple output systems with low resolution analog-to-digital converters (ADCs) at the base station. The nonlinearities introduced by the ADCs make the problem challenging: in particular, the existing linear detectors perform poorly. Also, the channel coding used in commercial wireless systems necessitates soft symbol detection to obtain satisfactory performance. In this paper, we present a low-complexity variational Bayesian (VB) inference procedure to jointly solve the (possibly correlated) channel estimation and soft symbol decoding problem. We present the approach in progressively more complex scenarios, including the case where even the channel statistics are not available at the receiver. Finally, we combine our proposed VB procedure with a belief propagation (BP) based channel decoder, which further enhances the performance without any additional complexity. We numerically evaluate the bit error rate (BER) and the normalized mean squared error (NMSE) in the channel estimates obtained by our algorithm as a function of various system parameters, and benchmark the performance against genie-aided and state-of-the-art receivers. The results show that VB procedure is a promising technique for the design of low-complexity advanced receivers in low resolution ADC based systems. [ABSTRACT FROM AUTHOR]

Path fading and non-line-of-sight (NLOS) signals constitute serious problems in the wireless localization process. These problems cause unpredictable degradation in the localization precision. In this paper, a novel wireless localization approach, which is based on twice receiving array signal spectra fusions and asymmetric second-order stochastic resonance (ASSR) networks, is proposed. By combining and repetitively processing the above two techniques, the receiving signal-to-noise ratio (SNR) can be enhanced. Additionally, the receiving array signal without the line-of-sight (LOS) component can be determined and removed from the spectra fusion process. The theoretical analyses presented verify the unbiasedness and asymptotic efficiency of the proposed twice receiving spectra fusion approach. Computer simulations demonstrate that the fused spectra can significantly improve the wireless localization precision compared with conventional and up-to-date localization methods, especially under low SNR conditions. [ABSTRACT FROM AUTHOR]

Multiple-input Multiple-output (MIMO) technologies play an important role in modern and future wireless communication systems as they can improve the capacity without increasing the bandwidth. MIMO detection is one of the key technologies for MIMO system designs. MIMO detection schemes based on Message Passing (MP) algorithms have attracted extensive attention in recent years. The MIMO detection scheme based on Expectation Propagation (EP), which is also a kind of MP algorithms, has been proved to achieve the Bayes-optimal performance under the conditions of large system limit and compression rate threshold. However, there is improvement space for the detection performance of the EP algorithm when the conditions are not satisfied, which are the common cases in the practical applications. In this paper, when the conditions of the large system limit and compression rate threshold are not satisfied, we analyze the influences of two factors, the initial parameters selection and the moment matching strategy, on the performance of EP based detection scheme. As a result, we propose an improved EP detection scheme based on optimizing the two factors. Simulation results show that the proposed scheme outperforms the original EP detection scheme in different MIMO scenarios. [ABSTRACT FROM AUTHOR]

Terahertz (THz) band has attracted considerable interest recently due to its superior high frequency and large available bandwidth. THz could act a vital part in the sixth generation (6G) mobile communication networks. In this paper, we introduce the downlink non-orthogonal multiple access (NOMA) technology into THz band small cell networks, where the total performance is optimized considering the two key enabling technologies. In order to decrease the energy consumption triggered by increasing of wireless services, we pay great attention to energy efficiency (EE) optimization and resource allocation in the THz-NOMA downlink systems by solving the subchannel assignment and power optimization. We first exploit a channel model for the THz-NOMA downlink system by using the key features of THz-NOMA networks. Then we utilize Dinkelbach-style algorithm to solve the resource allocation problem and decompose it into two subproblems. A subchannel assignment algorithm and a power optimization based on alternative direction method of multipliers (ADMM) algorithm are developed to get the solution. Finally, to embody the strengths of THz-NOMA performance, we compare our proposed schemes against the conventional schemes. Simulation results yield substantially higher EE and further prove the availability of our proposed schemes. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a coordinated multipoint (CoMP) beamforming and power control problem for base stations (BSs) with a massive number of antenna arrays under coarse quantization at low-resolution analog-to-digital converters (ADCs) and digital-to-analog converter (DACs). Unlike high-resolution ADC and DAC systems, non-negligible quantization noise that needs to be considered in CoMP design makes the problem more challenging. We first formulate total power minimization problems of both uplink (UL) and downlink (DL) systems subject to signal-to-interference-and-noise ratio (SINR) constraints. We then derive strong duality for the UL and DL problems under coarse quantization systems. Leveraging the duality, we propose a framework that is directed toward a twofold aim: to discover the optimal transmit powers in UL by developing iterative algorithm in a distributed manner and to obtain the optimal precoder in DL as a scaled instance of UL combiner. Under homogeneous transmit power and SINR constraints per cell, we further derive a deterministic solution for the UL CoMP problem by analyzing the lower bound of the SINR. Lastly, we extend the derived result to wideband orthogonal frequency-division multiplexing systems to optimize transmit power and beamformer for all subcarriers. Simulation results validate the theoretical results and proposed algorithms. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS)-empowered communication is one of the promising 6G technologies that allows the conversion of the wireless channel into an intelligent transmit entity by manipulating the impinging waves using man-made surfaces. In this paper, the potential benefits of using RISs are investigated for indoor/outdoor setups and various frequency bands (from sub 6 GHz to millimeter-waves). First, a general system model with a single RIS is considered and the effect of the total number of reflecting elements on the probabilistic distribution of the received signal-to-noise ratio and error performance is investigated under Rician fading. Also for this case, the path loss exponent is analyzed by considering empirical path loss models. Furthermore, transmission models with multiple RISs are developed and analyzed for indoor and outdoor non line-of-sight (NLOS) scenarios. The conventional RIS selection strategies are also integrated for systems equipped with multiple RISs for the first time. Through extensive simulations, it is demonstrated that the RIS-assisted systems provide promising solutions for indoor/outdoor scenarios at various operating frequencies and exhibit significant results in error performance and achievable data rates even in the presence of system imperfections such as limited range phase adjustment and imperfect channel phase estimation at RISs. [ABSTRACT FROM AUTHOR]

In this paper, we focus on intelligent reflecting surface (IRS) assisted multi-antenna communications with transceiver hardware impairments encountered in practice. In particular, we aim to maximize the received signal-to-noise ratio (SNR) taking into account the impact of hardware impairments, where the source transmit beamforming and the IRS reflect beamforming are jointly designed under the proposed optimization framework. To circumvent the non-convexity of the formulated design problem, we first derive a closed-form optimal solution to the source transmit beamforming. Then, for the optimization of IRS reflect beamforming, we obtain an upper bound to the optimal objective value via solving a single convex problem. A low-complexity minorization-maximization (MM) algorithm was developed to approach the upper bound. Simulation results demonstrate that the proposed beamforming design is more robust to the hardware impairments than that of the conventional SNR maximized scheme. Moreover, compared to the scenario without deploying an IRS, the performance gain brought by incorporating the hardware impairments is more evident for the IRS-aided communications. [ABSTRACT FROM AUTHOR]