Downlink Communication System Research Articles

A novel superposition coding scheme based on polar code for multi‐user detection in underwater acoustic OFDM communication system

SummarySuperposition coding (SC) is a non‐orthogonal multiple access (NOMA) scheme for the downlink communication system, which allows signals of different users to be stacked and forwarded simultaneously in the same frequency band. The codeword for each user is assigned a different weight at the transmitter to avoid signal conflicts and interference after stacking, and successive interference cancellation (SIC) is adopted to decode. A novel SC scheme based on polar code, suitable for the downlink multi‐user underwater acoustic (UWA) communication system using orthogonal frequency division multiplexing (OFDM), is proposed in this paper. Polar code is utilized to create a nested code structure that is divided into several subsets. We exploit this feature of the polar codes and assign each subset to the corresponding user in the channel coding process. The information bits are placed on the independent subset for each user, and the random bits are placed on the subset of other users while all the users share the same set of frozen bits. Then, the codewords are stacked with different weights. The selection range of power factors can be expanded through the double superposition of the coding and the power domains, and higher system throughput and fairness can be achieved. The simulation and tank experiment results significantly verify the effectiveness of the proposed scheme, making it most suitable for the downlink UWA multi‐user communication systems.

Enhanced Non-Orthogonal Multiple Access Performance Using Channel Coding for High-Altitude Platform System (HAPS)

The high-altitude platform system (HAPS) is a promising technology for providing high-speed data transmission and coverage for remote areas. Still, it suffers from unpredictable channel transmission, especially in the Rician channel. To overcome the issue in transmission, we used one channel coding strategy, namely the quasi-cyclic low-density parity-check (QC-LDPC). This study aims to evaluate the performance of power domain non-orthogonal multiple access (PD-NOMA), which allows multiple users to share the same spectrum in a downlink communication system from HAPS to three ground stations. We simulated the system using MATLAB simulation with different power allocation coefficients for every ground station. The simulation results showed that QC-LDPC codes can significantly lower the signal-to-noise ratio (SNR) required to achieve the same bit error rate (BER) as uncoded NOMA, especially in scenarios with uneven power allocation. The average improvement of QC-LDPC over uncoded NOMA was 8.4% in SNR. However, we also observed that NOMA is prone to domino errors, where decoding errors in one ground station can propagate and degrade the performance of the subsequent ground station. Furthermore, we found that power allocation significantly impacts the system performance, while the location and power allocation of the second ground station have a minor effect. Based on these findings, we conclude that QC-LDPC can enhance system performance in scenarios with low received power and that power allocation is a crucial factor for NOMA systems with multiple ground stations.

Efficient Constant Envelope Precoding for Massive MU-MIMO Downlink via Majorization-Minimization Method.

The practical implementation of massive multi-user multi-input-multi-output (MU-MIMO) downlink communication systems power amplifiers that are energy efficient; otherwise, the power consumption of the base station (BS) will be prohibitive. Constant envelope (CE) precoding is gaining increasing interest for its capability to utilize low-cost, high-efficiency nonlinear radio frequency amplifiers. Our work focuses on the topic of CE precoding in massive MU-MIMO systems and presents an efficient CE precoding algorithm. This algorithm uses an alternating minimization (AltMin) framework to optimize the CE precoded signal and precoding factor, aiming to minimize the difference between the received signal and the transmit symbol. For the optimization of the CE precoded signal, we provide a powerful approach that integrates the majorization-minimization (MM) method and the fast iterative shrinkage-thresholding (FISTA) method. This algorithm combines the characteristics of the massive MU-MIMO channel with the second-order Taylor expansion to construct the surrogate function in the MM method, in which minimizing this surrogate function is the worst-case of the system. Specifically, we expand the suggested CE precoding algorithm to involve the discrete constant envelope (DCE) precoding case. In addition, we thoroughly examine the exact property, convergence, and computational complexity of the proposed algorithm. Simulation results demonstrate that the proposed CE precoding algorithm can achievean uncoded biterror rate (BER) performance gain of roughly 1dB compared to the existing CE precoding algorithm and has an acceptable computational complexity. This performance advantage also exists when it comes to DCE precoding.

Energy-Efficient RIS-Enabled SISO-OFDMA Communication via Lower Bound Optimization

The pursuit of energy-efficient solutions in the context of reconfigurable intelligent surface (RIS)-assisted wireless networks has become imperative and transformative. This paper investigates the integration of RIS into an orthogonal frequency-division multiple access (OFDMA) framework for multi-user downlink communication systems. We address the challenge of jointly optimizing RIS reflection coefficients alongside OFDMA frequency and power allocations, with the aim of maximizing energy efficiency. This optimization is subject to specific quality-of-service (QoS) requirements for each user equipment (UE) and a constraint on transmission power and the RIS phase shift matrix. To address this complex optimization problem, we propose a novel practical and low-complexity approach that is based on optimizing a computationally efficient and numerically tractable lower bound on energy efficiency. The numerical results highlight the effectiveness of our approach, demonstrating a substantial increase in energy efficiency compared to scenarios without RIS, with random RIS integration, and with the scheme using the Genetic Algorithm (GA).

A low-power anti-interference parallel downlink communication system design

The Internet of Things (IoT) has seen rapid advancements and widespread deployment of wireless devices recently. To pursue the long-term deployment goal of the Internet of Things, a lot of work in recent years has focused on low-power devices, such as backscatter systems. However, they face two key challenges, unequal uplink and downlink communication range, and weak end devices’ inability to handle downlink conflicts and networking. In this paper, we propose a µW-level downlink receiving system, which enhances the anti-interference and anti-conflict capabilities of low-power end devices. We also present a state machine model for networking capabilities. We implemented the prototype system using discrete components and FPGA and conducted experiments. The result shows that our system achieves a downlink communication range of over 250m at a 1kbps data rate with 1% BER and increased by more than 10 times compared to conventional backscatter receivers. The power consumption is 73.6 µW.

TD3-Based Optimization Framework for RSMA-Enhanced UAV-Aided Downlink Communications in Remote Areas

The need for reliable wireless communication in remote areas has led to the adoption of unmanned aerial vehicles (UAVs) as flying base stations (FlyBSs). FlyBSs hover over a designated area to ensure continuous communication coverage for mobile users on the ground. Moreover, rate-splitting multiple access (RSMA) has emerged as a promising interference management scheme in multi-user communication systems. In this paper, we investigate an RSMA-enhanced FlyBS downlink communication system and formulate an optimization problem to maximize the sum-rate of users, taking into account the three-dimensional FlyBS trajectory and RSMA parameters. To address this continuous non-convex optimization problem, we propose a TD3-RFBS optimization framework based on the twin-delayed deep deterministic policy gradient (TD3). This framework overcomes the limitations associated with the overestimation issue encountered in the deep deterministic policy gradient (DDPG), a well-known deep reinforcement learning method. Our simulation results demonstrate that TD3-RFBS outperforms existing solutions for FlyBS downlink communication systems, indicating its potential as a solution for future wireless networks.

Energy-efficient resource allocation and user grouping for multi-IRS aided MU-MIMO system

In this paper, we consider a multiple-intelligent reflecting surface (IRS)-aided multi-user multiple-input-multiple-output (MU-MIMO) down-link communication system, wherein a base station (BS), equipped with multiple antennas, serves massive single-antenna users. In order to mitigate high inter-user interference, we divide all the users into a single near-user (NU) group and multiple cell-edge user (CEU) groups based on their connection with BS. In particular, we assign a single IRS for each CEU group such that the BS communicates and serves the set of CEUs using their corresponding IRS. Subsequently, we formulate a problem of energy-efficient resource allocation design subject to optimal beamforming design at BS and multiple IRS under given power constraints. Due to the non-convexity of the formulated resource allocation problem, we proposed two different alternating optimization frameworks which solve the joint optimization problem based on 1) minimum mean square error (MMSE) and Riemannian conjugate gradient (RCG) and 2) fractional programming and successive convex approximation techniques for active beamforming vectors at the BS and passive beamforming vectors for IRSs, respectively. Simulation results confirm that the MMSE-RCG-based resource allocation design attains fast convergence when compared to sequential fractional programming (SFP) based solution. Moreover, the MMSE-RCG attains better energy efficiency whereas the SFP renders better spectral performance. Nevertheless, both the proposed solution achieve 70%–80% better performance than random phase-shift settings.

Joint Design of a Simultaneous Reflection and Transmission RIS in Mode-Switching Mode to Assist NOMA Systems.

Simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) can reflect signals and transmissive signals simultaneously and can extend the coverage of signals. A conventional RIS mainly focuses on the case where the signal source and the target are on the same side. In this paper, a STAR-RIS-assisted non-orthogonal multiple access (NOMA) downlink communication system is considered to maximize the achievable rate for users by jointly optimizing the power-allocation coefficients, active beamforming, and STAR-RIS beamforming under the mode-switching (MS) protocol. The critical information of the channel is first extracted using the Uniform Manifold Approximation and Projection (UMAP) method. Based on the key extracted channel features, STAR-RIS elements and users are clustered individually using the fuzzy C-mean clustering (FCM) method. The alternating optimization method decomposes the original optimization problem into three sub-optimization problems. Finally, the sub-problems are converted to unconstrained optimization methods using penalty functions for the solution. Simulation results show that when the number of elements of RIS is 60, the achievable rate of the STAR-RIS-NOMA system is about 18% higher than that of the RIS-NOMA system.

UAV Swarm-Enabled Aerial Reconfigurable Intelligent Surface: Modeling, Analysis, and Optimization

Reconfigurable intelligent surface (RIS) offers tremendous spectrum-and-energy efficiency in wireless networks. With the agility and mobility of an unmanned aerial vehicle (UAV), RIS can be mounted on a UAV to enable three-dimensional (3D) signal reflections, reliable air-ground connections, and higher configuration flexibility. However, the scalability of the aperture gain and the spatial multiplexing could not be guaranteed in a single UAV-enabled aerial RIS due to UAV’s limited payload and line-of-sight-dominated air-ground connection. In this paper, we study a UAV swarm-enabled aerial RIS (SARIS)-assisted downlink communication system. The objective of the considered SARIS system is to maximize the weighted sum-rate of ground users by designing the transmit beamforming at the base station (BS), the phase shifts of SARIS reflecting elements, and SARIS 3D placement. For joint BS and SARIS beamforming design, we introduce two beamforming schemes with low computational complexity. For SARIS placement design, the optimal SARIS 3D position is obtained by leveraging the tools from stochastic geometry and considering the distributions of ground users. Simulation results confirm the validity of the analytical derivations. In particular, the SARIS placement plays a vital role in the system performance when the distances between users and the BS increase.

Enhancing Physical Layer Security of Cooperative Nonorthogonal Multiple Access Networks via Artificial Noise

The massive connectivity requirement and security issues have become major factors restricting the further development of the Internet of Things. Nonorthogonal multiple access (NOMA) can be combined with physical layer security (PLS) to achieve massive connectivity and secure transmission. This article investigates the PLS performance for a downlink communication system over Nakagami-m fading channels, with full-duplex (FD) cooperative NOMA transmission aided by artificial noise (AN). While direct communication is built between the base station and two NOMA users, the strong user is employed as an FD relay as well as the jammer to enhance the PLS of the legitimate transmission in the presence of a passive eavesdropper (Eve). Closed-form analytical expressions in terms of the outage probability of the legitimate users and the intercept probability of Eve are derived to evaluate the security–reliability trade-off (SRT) of the proposed scheme. Monte Carlo simulations are provided to validate the veracity of the theoretic analyses and illustrate that the proposed scheme is superior in terms of SRT to the benchmark schemes in the low SNR region. Furthermore, the results reveal that the SRT performance of the two NOMA users can be enhanced through a proper AN-bearing ratio and power allocation optimization.

Outage probability of NOMA systems with receive antenna selection in [formula omitted]-[formula omitted] fading channels

This article considers power-domain non-orthogonal multiple access (NOMA) for downlink communication systems that involve multiple users. The base station, equipped with a single transmit antenna, communicates simultaneously with multiple users, each equipped with a single receive antenna. The article examines the system’s outage probability (OP) performance in α−μ generalized fading channels. The article first derives the instantaneous signal-to-interference-and-noise ratio (SINR) and then obtains the OP expression for each user in a closed form. The derived expression for OP is general and includes special cases such as Nakagami-m, Weibull, Gamma, Rayleigh, and Exponential distributions. This α−μ expression helps quantify the improvement of the OP performance. In order to improve the OP performance, multiple antennas are included for the users, and then receive antenna selection (RAS) scheme is employed. Finally, the theoretical OP expressions are verified via Monte Carlo simulations.

Beamforming design for max‐min SINR in RIS‐based hybrid relaying

AbstractReconfigurable intelligent surface (RIS) technology is regarded as one of the important technologies for future 6G mobile communication networks. However, RIS can only passively reflect signals, rather than actively process received signals like the traditional relay. Therefore, a hybrid decode‐and‐forward (DF) relay and RIS‐assisted multiple‐input single‐output (MISO) multiuser downlink communication system is considered to combine the advantages of both. Then the beamforming at the base station (BS), the DF relay, and the phase vector of the RIS elements is jointly designed, aiming at achieving max‐min signal‐to‐interference‐plus‐noise ratio (SINR). Due to the non‐convexity caused by coupling between the beamforming vectors, the optimization problem is split into three semidefinite relaxation (SDR) sub‐problems, and then the alternate optimization method is adopted to solve the non‐convex problem. The numerical results verify the effectiveness and superiority of the proposed optimization algorithm in improving system performance compared with other benchmark schemes.

On the Performance of STAR-RIS-Aided NOMA at Finite Blocklength

Simultaneous refracting/transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) has emerged as a potential technology for future-generation wireless communication that enhances the signal quality and provides 360∘ coverage area. In this letter, we provide a finite blocklength (FBL) analysis of a STAR-RIS-aided downlink communication system with non-orthogonal multiple access (NOMA), where the base station (BS) transmits a superimposed signal to two users with the aid of a STAR-RIS. First, we derive the probability density function (PDF) and cumulative distribution function (CDF) of the signal-to-interference-plus-noise ratio (SINR) of each user, and then we analyze the system performance by deriving analytical expressions for their block error rate (BLER) and goodput. Finally, using Monte-Carlo simulations, we validate the accuracy of the derived analytical expressions, and highlight the impact of key system parameters such as blocklength, and the number of refracting and reflecting elements on the system performance.

A Resource Allocation Policy for Downlink Communication in Distributed IRS Aided Multiple-Input Single-Output Systems

As a technology for 6G wireless communications, Intelligent Reflecting Surfaces (IRSs) are considered as a promising solution to boost the network capacity, spectrum and coverage in multiusers’ downlink communication systems. The users in blockage and cell edge areas can utilize this technology for data transfer purpose. In this paper, a machine learning-based policy optimization for downlink communication in distributed IRS aided multiple-input single-output (MISO) systems is proposed. Three categories of users are considered, namely, users who can utilize only the direct links, blockage area users who can utilize only the IRS links, and cell edge or poor link quality of users who can utilize both the direct and IRS links. The sum rate maximization problem is formulated to derive the optimal policy (i.e. communication link, IRS selection, power allocation and reflection coefficients) for those users, considering the IRS selection, link quality, power allocation and IRS reflection constraints. The proposed methods to achieve the optimal policy include reinforcement learning-based model with binary decision tree-based user categories, maximum posterior probability-based IRS selection, fractional programming method-based power and IRS coefficient allocation, and value function-based policy optimization. Through simulations, the sum data rate and energy efficiency performances of different categories of users are obtained and discussed.

Integrated Multicast and Unicast Transmission in IRS-NOMA Networks

This paper considers an integrated multicast and unicast downlink communication system using the non-orthogonal multiple access (NOMA) scheme assisted by an intelligent reflecting surface (IRS). We aim to maximize the unicast data rate while keeping the multicast data rates above a target level by adjusting the reflecting elements of the IRS. The corresponding formulated problem is a nonconvex quadratically constrained quadratic program (QCQP), which is NP-hard. We propose a global optimal algorithm based on branch and bound (BB) and a low-complexity suboptimal algorithm based on semidefinite relaxation (SDR). The simulation results show that the proposed IRS-NOMA scheme outperforms IRS-assisted orthogonal multiple access (OMA) and IRS-NOMA with random phases. Besides, the suboptimal algorithm achieves a better tradeoff between performance and complexity.

Analysis of Fair-NOMA Power Allocation: a Comparative Study Between NOMA and OMA Systems

Non-Orthogonal Multiple Access (NOMA) system has been very interesting technique recommended for the fifth generation (5G) of wireless mobile communication networks. The strategy of a suitable multiple access technique is one of the most important aspects in improving the system capacity. Multiple access techniques can broadly be categorized into two different approaches, namely: OMA and NOMA. In this paper a downlink communication system composed of a base station and M users where each one is equipped with a single antenna is considered, and multiple users system are characterized by multipath communication known as Rayleigh fading channel which can be described by a complex fading channel coefficient. It is well known that NOMA fairness feature implies that, with NOMA approach, near and far mobile users from a base station are able to achieve at least the possible information capacity similarly to OMA users. Fair-NOMA is described by fairness index (F) and a power allocation coefficient (a) limiting the fairness region R bounded by extreme values amin and amax, this fairness index is given as a function of NOMA power allocation coefficient, SNR ratio and channel gains of NOMA users. Maximum fairness index is obtained for a power allocation coefficient belonging to the fairness region, which is large for weak SNR ratios, and slight for high levels. In addition, the calculation of NOMA and OMA ergodic capacities at fairness bounds, indicates that NOMA approach always outperforms OMA one. Further, fairness index evolution is considered in function of channel gains, power allocation coefficients and SNR ratio levels, giving as result, optimal fairness can be reached by a judicious power allocation to the furthest user from the base station.

Ergodic Rate Analysis and Phase Design of STAR-RIS Aided NOMA With Statistical CSI

In this letter, we consider a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided non-orthogonal multiple access (NOMA) downlink communication system. The base station (BS) is a uniform linear array (ULA) consisting of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -elements. The expressions of the statistic of signal-to-interference-noise ratio (SINR) are derived with the statistical characteristics of the channels and they are maximized to design the phase shift matrices for reflection and transmission. Furthermore, the approximate analytical expressions of the ergodic rate are derived and the asymptotic performance is analyzed. It is found from the approximate analytical expressions that increasing the size of the ULA at BS and the STAR-RIS size can effectively improve the ergodic rate of the system. The simulation results validate the validity of the theoretical analysis and the design of the phase shift matrices.

Ergodic Capacity Analysis of Downlink Communication Systems under Covariance Shaping Equalizers

Advances in higher-end spectrum utilization has enabled user equipment to dock multiple antenna elements, and hence make use of selectivity via equalization in new generation of mobile networks. The equalization can exploit channel statistics to shape covariance matrices, and hence improve network performance at the physical layer of these networks by projecting segregated signals to non-overlapping subspaces. We propose to establish the promise of covariance shaping method by incorporating the equalizers in the modelling of a downlink multi-user multiple-input multiple-output (MU-MIMO) systems and thereby characterizing a key performance indicator, namely, the sum ergodic capacity. This is achieved by utilizing a residue theory approach which can account for indefinite eigenvalues. The system modelling is generic in a sense that it requires the base station (BS) to only have second order statistics of the channel rather than instantaneous knowledge. Furthermore, the BS incorporates a transmit beamformer design to enhance the ergodic capacity and feedforward the information of covariance shaping equalizers. Search method for transmit beamforming is also proposed which shows a promising three fold increase in sum ergodic capacity at signal-to-noise ratio of 10 dB for the considered MU-MIMO system. Proposed characterization of the system is authenticated using simulation means, and a comparative analysis of transmit beamformer designs on the sum ergodic rate is showcased.

Low-Complexity Beamforming Algorithms for IRS-Aided Single-User Massive MIMO mmWave Systems

This paper considers intelligent reflecting surface (IRS)-aided single-user (SU) massive multiple-input multiple-output (mMIMO) millimeter wave (mmWave) downlink communication system. We aim to maximize the achievable spectral efficiency by separately designing the passive beamforming and active precoding (combining) through a decoupling strategy to reduce computational complexity. We propose two algorithms for passive beamforming design, which are followed by singular value decomposition (SVD) of the effective channel matrix to generate the active precoding and combining matrices at the bases station (BS) and user equipment (UE), respectively. The first algorithm employs the SVD of the BS-IRS and the IRS-UE channel matrices to generate the unitary matrices. These matrices are used to develop the optimization problem, which is solved via a Riemannian conjugate gradient (RCG)-based algorithm, yielding a passive beamforming vector. In the second algorithm, we propose a greedy-search (GS)-based method to select the array response vectors and their corresponding path gains of the mmWave channels between the BS (IRS) and IRS (UE) required to formulate the optimization problem, which is also solved via the RCG-based algorithm, resulting in a passive beamforming vector. The simulation results show that the proposed schemes achieve an improved trade-off between the spectral efficiency and computational complexity.

Cooperative beamforming design for double-IRS-assisted MISO communication system

Intelligent reflecting surface (IRS) has arisen as a promising technology to reconfigure the wireless propagation environment cost-effectively. Most of the existing works on IRS focused on the passive beamforming (PB) optimization and performance enhancement without considering the multiple inter-IRS links cooperation that did not reveal the full preponderance of the multi-IRS-assisted reconfigurable communication system. In this work, we investigate a double-IRS-assisted multiple input single output (MISO) downlink communication system with the active beamforming (AB) and the cooperative PB design in the absence of direct link. Taking both the double-reflection links and the single-reflection links into account, the AB at the base station (BS) and the cooperative PB at two IRSs are jointly optimized to maximize the weight sum rate (WSR) under the constraint of the transmit power. To tackle the problem, we propose the double-IRS-assisted fractional programming block coordinate descent (D-FPBCD) method to find the sub-optimal solution with low complexity. We first reconstruct the original issue as a tractable one by the closed-form fractional programming (FP) approach, then, the prox-linear block coordinate descent (BCD) and successive convex approximation (SCA) techniques are used to find the sub-optimal solution. Finally, simulation results demonstrate the effectiveness of the proposed double-IRS-assisted wireless communication scheme.