Multiple-antenna Base Station Research Articles

RIS-Aided SCMA-Based SWIPT Systems: Design and Optimization

The amalgamation of sparse code multiple access (SCMA) and simultaneous wireless information and power transfer (SWIPT) is envisioned to be a promising solution to massive connectivity while providing both information and power to myriads of wireless machines and sensors in Internet-of-Things (IoT) application. However, the benefit of the SCMA-based SWIPT system has not been fully exploited yet, especially when the communications link is hostile. Fortunately, the propagation-induced impairment can be mitigated by the emerging technique of reconfigurable intelligent surface (RIS). In this paper, we investigate the beneficial role of RIS in SCMA-based SWIPT systems, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K$</tex-math></inline-formula> single-antenna information receivers and one signal-antenna energy receiver are served by a multiple-antenna base station over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$J$</tex-math></inline-formula> orthogonal subcarriers with the aid of RIS. We propose transmit power minimization algorithms for both <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i)</i> the perfect and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii)</i> the imperfect channel state information (CSI) scenarios, by jointly optimizing the codebook assignment, the BS active beamforming, as well as RIS reflection coefficients, relying on advanced techniques both of alternating optimization and of successive convex approximations, and on the robust design framework. Furthermore, we compare and evaluate the detection performance of the system considered. The numerical results demonstrate that our proposed RIS-aided SCMA-based SWIPT system significantly outperforms the conventional SCMA-based SWIPT system without RIS and is capable of adapting to the imperfect full channel estimation results.

On secrecy performance analysis of multi-antenna STAR-RIS-assisted downlink NOMA systems

To accommodate the stringent requirements of enhanced coverage quality and improved spectral efficiency, simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided communication has been perceived as an interesting research topic. This paper investigates a downlink STAR-RIS-aided non-orthogonal multiple access (NOMA) system, where a STAR-RIS is deployed to enhance the transmission qualities between users and a multiple-antenna base station (BS). The considered STAR-RIS utilizes the energy splitting (ES) protocol to serve a pair of NOMA users located at both sides of STAR-RIS. Based on the ES protocol, each reconfigurable element can operate in the modes of transmission and reflection simultaneously. In an effort to characterize the secrecy performance, we first derive the closed-form expressions of secrecy outage probability (SOP) for STAR-RIS-aided NOMA system. Then, the asymptotic performance of the derived SOP is analyzed. For gleaning further insights, secrecy diversity order (SDO) is derived according to the asymptotic approximation in the high signal-to-noise ratio and main-to-eavesdropper ratio regimes. As a further advance, the system parameters are optimized to minimize the SOP of the system. Our analytical results demonstrate that the multiple-antenna BS has almost no impact on SDO for STAR-RIS-aided NOMA system. In simulations, it is demonstrated that the theoretical results match with the simulation results very well and the SOP of STAR-RIS-aided NOMA is less than that of conventional orthogonal multiple access (OMA) system obviously.

Error Performance Analysis of Multiuser Detection in Uplink-NOMA With Adaptive M-QAM

This letter provides a generalized performance analysis for the multi-user uplink-NOMA system with adaptive square quadrature amplitude modulation (QAM) over Rayleigh fading channels. Motivated by the massive IoT connections and unavailability of orthogonal resources for each node, we consider a multi-access scheme where multi-users with single-antenna transmit data to a multiple-antenna base station through the same resource block. By taking advantage of combining diversity paths with the proposed joint maximum-likelihood detector (JMLD), a closed form expression for the upper bound of bit error rate (BER) is obtained. Despite the number of users or the order of modulation, the analytical results endorsed via computer simulations reveal the ability of the MRC-JMLD detector to discard the error floor completely. Moreover, the simulation results show that the MRC-JMLD surpasses its counterparts significantly and ensures a full diversity order.

Cooperative 3D Beamforming for Small-Cell and Cell-Free 6G Systems

Three dimensional (3D) resource reuse is an important design requirement for the prospective sixth generation (6 G) wireless communication systems. Hence, we propose a cooperative 3D beamformer for use in 3D space. Explicitly, we harness multiple base station antennas for joint zero forcing transmit pre-coding for beaming the transmit signals in specific 3D directions. The technique advocated is judiciously configured for use in both cell-based and cell-free wireless architectures. We evaluate the performance of the proposed scheme using the metric of Volumetric Spectral Efficiency (VSE). We also characterized the performance of the scheme in terms of its spectral efficiency (SE) and Bit Error Rate (BER) through extensive simulation studies.

Algorithm Unrolling for Massive Access via Deep Neural Networks With Theoretical Guarantee

Massive access is a critical design challenge of Internet of Things (IoT) networks. In this paper, we consider the grant-free uplink transmission of an IoT network with a multiple-antenna base station (BS) and a large number of single-antenna IoT devices. Taking into account the sporadic nature of IoT devices, we formulate the joint activity detection and channel estimation (JADCE) problem as a group-sparse matrix estimation problem. This problem can be solved by applying the existing compressed sensing techniques, which however either suffer from high computational complexities or lack of algorithm robustness. To this end, we propose a novel algorithm unrolling framework based on the deep neural network to simultaneously achieve low computational complexity and high robustness for solving the JADCE problem. Specifically, we map the original iterative shrinkage thresholding algorithm (ISTA) into an unrolled recurrent neural network (RNN), thereby improving the convergence rate and computational efficiency through end-to-end training. Moreover, the proposed algorithm unrolling approach inherits the structure and domain knowledge of the ISTA, thereby maintaining the algorithm robustness, which can handle non-Gaussian preamble sequence matrix in massive access. With rigorous theoretical analysis, we further simplify the unrolled network structure by reducing the redundant training parameters. Furthermore, we prove that the simplified unrolled deep neural network structures enjoy a linear convergence rate. Extensive simulations based on various preamble signatures show that the proposed unrolled networks outperform the existing methods in terms of the convergence rate, robustness and estimation accuracy.

Exploiting Reconfigurable Intelligent Surface-Based Uplink/Downlink Wireless Systems

This paper analyzes the performance of an uplink/downlink reconfigurable intelligent surface (RIS)-based wireless system with a multiple-antenna base station (B), where the RIS selection strategy is considered to alleviate the overhead and resources. With the goal of enhancing system performance, we consider maximal-ratio-combining (MRC) and selection-combining (SC) for the uplink transmission and maximum-ratio-transmission (MRT) along with beamforming design for the downlink transmission, where two methods of direct-path beamforming design (DBD) and reflective-path beamforming design (RBD) are proposed. We also quantify the impact of uncertain phase shift (UPS) and optimal phase shift (OPS) alignments. Accordingly, closed-form expressions for outage probability (OP) of each uplink and downlink scenario are derived. Numerical results show that, in the uplink transmission, adopting MRC at the B and OPS at RIS provides the best performance. For small antenna settings, using SC-enabled OPS provides outstanding performance when compared to employing MRC-integrated UPS. In downlink transmission, RBD achieves better performance than that of DBD. Similar to the uplink transmission, employing MRT at the B and OPS at the RIS also attains superior performance when compared to UPS.

Robust Active and Passive Beamformer Design for IRS-Aided Downlink MISO PS-SWIPT With a Nonlinear Energy Harvesting Model

This paper optimizes the energy consumption of the downlink of a multiple-antenna base station (BS) transmitting to several single-antenna users. The BS utilizes simultaneous wireless information and power transfer (SWIPT) while receivers apply power-splitting (PS) with a nonlinear energy harvesting model leading to PS-SWIPT. We use an intelligent reflecting surface (IRS) and propose a joint design to optimize the active data and the BS&#x2019;s energy beamformers, IRS&#x2019;s passive beamformers, and the receivers&#x2019; PS ratios under perfect and imperfect CSI availability. In particular, the total BS transmit power is minimized while guaranteeing a minimum rate and harvested energy for each receiver. We apply the block coordinate descent (BCD) method to optimize active and passive beamformers iteratively. We enforce the rank-one constraint and solve the corresponding optimization problem via successive convex approximation (SCA) for accurate semidefinite relaxations. Furthermore, we propose a worst-case robust design for the imperfect CSI case and reformulate this problem with infinitely many constraints. With the BCD method, the problem is iteratively solved via semidefinite programming (SDP) and a second sub-problem with a linear objective and quadratic matrix inequalities, which is also solved via SCA. Numerical results show significant improvements (e.g., 30&#x0025; decrease in transmit power) than those of no-IRS and IRS with random phase shifts.

New generalized zero forcing beamforming for serving more users in energy-harvesting enabled networks

This paper considers a multi-user wireless communication network supported by a multiple-antenna base station (BS), where the users who are located sufficiently close to the BS employ wireless energy harvesting (EH) to replenish their energy needs. The objective of this work is to design an efficient beamforming to maximize the minimum throughput among all the information users (IUs), subject to EH constraints. In this regard, transmit time-switching approach is employed, where energy and information are transmitted over different fractions of a time-slot. To achieve efficient EH, a conjugate beamforming (matched filtering) is applied. To design efficient information beamforming for max–min throughput optimization, conventional zero-forcing (ZF) beamforming can be adopted, however, it will not suppress multi-user interference if the number of users is greater than the number of antennas at the BS. To this end, different from the existing works which employ regularized zero-forcing (RZF) beamforming, this work proposes a new generalized zero-forcing (GZF) beamforming, which promises better max–min throughput compared to that achieved by the RZF beamforming. A new path-following algorithm is developed to achieve max–min throughput optimization by GZF beamforming, which is based on a simple convex quadratic program over each iteration.

Joint Transmit Waveform and Receive Filter Design for Dual-Function Radar-Communication Systems

In this paper, the problem of joint transmit waveform and receive filter design for dual-function radar-communication (DFRC) systems is studied. The considered system model involves a multiple antenna base station (BS) of a cellular system serving multiple single antenna users on the downlink. Furthermore, the BS simultaneously introduces sensing capabilities in the form of point-like target detection from the reflected return signals in a signal-dependent interference environment. A novel framework based on constrained optimization problems is proposed for the joint design of the transmit waveform and the radar receive filter such that different constraints related to the power amplifiers and the radar waveform are satisfied. In contrast to the existing approaches in the DFRC systems’ literature, the proposed approach does not require the knowledge of a predetermined radar beampattern in order to optimize the performance of the radar part through its approximation. Instead, a beampattern is generated by maximizing the radar receive signal-to-interference ratio (SINR) thus, enabling a more flexible design. Moreover, the radar receive filter processing and its optimization is considered for the first time on DFRC systems, enabling the effective exploitation of the available degrees of freedom in the radar receive array. Efficient algorithmic solutions with guaranteed convergence are developed for the defined constrained nonconvex optimization problems. The effectiveness of the proposed solutions is verified via numerical results.

Design of novel approach for emerging power-domain superposition coding (SC)-using hybrid NOMA-OFDM for 5G communications

PurposeThe suggested work examines the latest developments such as the techniques employed for allocation of power, browser techniques, modern analysis and bandwidth efficiency of nonorthogonal multiple accesses (NOMA) in the network of 5G. Furthermore, the proposed work also illustrates the performance of NOMA when it is combined with various techniques of wireless communication namely network coding, multiple-input multiple-output (MIMO), space-time coding, collective communications, as well as many more. In the case of the MIMO system, the proposed research work specifically deals with a less complex recursive linear minimum mean square error (LMMSE) multiuser detector along with NOMA (MIMO-NOMA); here the multiple-antenna base station (BS) and multiple single-antenna users interact with each other instantaneously. Although LMMSE is a linear detector with a low intricacy, it performs poorly in multiuser identification because of the incompatibility between LMMSE identification and multiuser decoding. Thus, to obtain a desirable iterative identification rate, the proposed research work presents matching constraints among the decoders and identifiers of MIMO-NOMA.Design/methodology/approachTo improve the performance in 5G technologies as well as in cellular communication, the NOMA technique is employed and contemplated as one of the best methodologies for accessing radio. The above-stated technique offers several advantages such as enhanced spectrum performance in contrast to the high-capacity orthogonal multiple access (OMA) approach that is also known as orthogonal frequency division multiple access (OFDMA). Code and power domain are some of the categories of the NOMA technique. The suggested research work mainly concentrates on the technique of NOMA, which is based on the power domain. This approach correspondingly makes use of superposition coding (SC) as well as successive interference cancellation (SIC) at source and recipient. For the fifth-generation applications, the network-level, as well as user-experienced data rate prerequisites, are successfully illustrated by various researchers.FindingsThe suggested combined methodology such as MIMO-NOMA demonstrates a synchronized iterative LMMSE system that can accomplish the optimized efficiency of symmetric MIMO NOMA with several users. To transmit the information from sender to the receiver, hybrid methodologies are confined to 2 × 2 as well as 4 × 4 antenna arrays, and thereby parameters such as PAPR, BER, SNR are analyzed and efficiency for various modulation strategies such as BPSK and QAMj (j should vary from 8,16,32,64) are computed.Originality/valueThe proposed hybrid MIMO-NOMA methodologies are synchronized in terms of iterative process for optimization of LMMSE that can accomplish the optimized efficiency of symmetric for several users under different noisy conditions. From the obtained simulated results, it is found, there are 18%, 23% 16%, and 8% improvement in terms of Bit Error Rate (BER), Least Minimum Mean Squared Error (LMMSE), Peak to Average Power Ratio (PAPR), and capacity of channel respectively for Binary Phase Shift Key (BPSK) and Quadrature Amplitude Modulation (QAM) modulation techniques.

Optimization of Rate Allocation and Power Control for Rate Splitting Multiple Access (RSMA)

In this paper, the sum-rate maximization problem is studied for wireless networks that use downlink rate splitting multiple access (RSMA). In the considered model, the base station (BS) divides the messages that can be transmitted to its users into a “private” part and a “common” part. Here, the common message is a message that multiple users want to receive and the private message is a message that is dedicated to only a specific user. The RSMA mechanism enables a BS to adjust the split of common and private messages so as to control the interference by decoding and treating interference as noise and, thus optimizing the data rate of users. To maximize the users' sum-rate, the network can determine the rate allocation for the common message to meet the rate demand, and adjust the transmit power for the private message to reduce the interference. This problem is formulated as an optimization problem whose goal is to maximize the sum-rate of all users. To solve this nonconvex maximization problem with a single-antenna BS, the optimal power used for transmitting the private message to the users is first obtained in closed form for a given rate allocation and common message power. Based on the optimal private message transmit power, the optimal rate allocation is then derived under a fixed common message transmit power. Subsequently, an iterative algorithm is proposed to obtain a suboptimal solution of common message transmit power. To solve this nonconvex maximization problem with a multiple-antenna BS, a successive convex approximation method is utilized. Simulation results show that the RSMA can achieve up to 15.6% and 21.5% gains in terms of data rate compared to non-orthogonal multiple access (NOMA) and orthogonal frequency-division multiple access (OFDMA), respectively.

Joint design of transmit beamforming, IRS platform, and power splitting SWIPT receivers for downlink cellular multiuser MISO

A multiple antenna base station (BS) with an intelligent reflecting surface (IRS) platform, and several single antenna users are considered in the downlink mode. Simultaneous wireless information and power transfer (SWIPT) is utilized by the BS via transmit beamforming to convey information and power to all devices. Each device applies power splitting (PS) to dedicate separate parts of received power to information decoding and energy harvesting. We formulate a total transmit power minimization problem to jointly design the BS beamforming vectors, IRS phase shifts, and PS ratios at the receivers subject to minimum rate and harvested energy quality of service (QoS) constraints at all the receivers. First, we develop a block coordinate descent algorithm, also known as alternating optimization that can decrease the objective function in every iteration with guaranteed convergence. Afterwards, two low-complexity sub-optimal algorithms that rely on well-known maximum ratio transmission and zero-forcing beamforming techniques are introduced. These algorithms are beneficial when the number of BS antennas and/or number of users is large, or coherence times of channels are small. Simulations corroborate the expectation that by deploying a passive IRS, BS transmit power can be reduced by 10–20 dBw while maintaining similar guaranteed QoS. Furthermore, even the proposed sub-optimal algorithms outperform the globally optimal SWIPT solution without IRS for a modest number of IRS elements.

Coverage Analysis and Scaling Laws in Ultra-Dense Networks

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.

Reconfigurable Intelligent Surfaces for Energy Efficiency in Multicast Transmissions

Reconfigurable Intelligent surface (RIS), which can induce phase shift of the received signals and then forward them by its reflecting elements, possesses high energy efficiency (EE). This letter studies the EE for the RIS-assisted multicast communication. A multiple-antenna base station (BS) delivers common messages to a group of mobile users (MUs), The RIS is placed to maintain the transmission. First, this letter analyzes the equivalent multicast channel and total power consumption to formulate an EE maximization problem. Then, this letter proposes the functional algorithms by fractional programming and alternating optimization to obtain a locally optimal solution for this problem. Lastly, we show asymptotic behaviors of the EE when the numbers of reflecting elements, antennas, and MUs go to infinity.

Performance of downlink NOMA with multiple antenna base station, full-duplex and D2D transmission

The implementation of non-orthogonal multiple access (NOMA) and transmit antenna selection (TAS) technique has considered in this paper since TAS-aware base station (BS) provides the low cost, low complexity, and high diversity gains. In this paper, we investigate performance of two users by deriving outage probability. The system performance benefits from design of TAS and full-duplex (FD) scheme applied at NOMA users, and bandwidth efficiency will be enhanced although self-interference exists due to FD. The main contribution lies in the exact expressions of outage probability which are derived to exhibit system performance. Different from the simulated parameters, the analytical results show that increasing number of transmit antennas at the BS is way to improve system performance.

Joint TS Beamforming and Hybrid TS-PS Receiving Design for SWIPT Systems

Simultaneously wireless information and power transfer technology enables information and energy to be transmitted over the same radio frequency (RF) signal. We investigate a multiple input simple output (MISO) system where the multiple-antenna base station not only transmits information to single-antenna users, but also supplies all power they need. The same beamforming at base station under two modes of energy transfer and information transmission causes the problem of low system energy efficiency. To solve this, we put forward a novel transmission scheme where beamforming is divided by time switching (TS) into two parts, energy beamforming and information beamforming, and users receive by hybrid time switching and power splitting (hybrid TS-PS) correspondingly. Under constraints of information and energy, we aim to achieve the maximal energy efficiency by jointly optimize power splitting, time allocation, beamforming for energy transfer and information transmission phase respectively. In the solving process, we transfer the maximal energy efficiency problem into the minimal energy consumption problem, analyze the feasibility, then prove the existing of optimal solution. Furthermore, we put forward a semidefinite relaxation (SDR) based algorithm to solve the problem optimally and two sub-optimal designs to simplify computing complexity. Simulation results illustrate that our proposed design can achieve the optimal energy efficiency and prove the asymptotic optimality of two sub-optimal solutions.

Beamforming Optimization for Intelligent Reflecting Surfaces without CSI

This letter considers the communication between a multiple antenna Base Station (BS) and a single antenna user, assisted by an Intelligent Reflecting Surface (IRS). Due to the large number of elements at the IRS, acquiring Channel State Information (CSI) requires many radio-frequency chains and considerable training overhead, what is limiting in practice. We aim to optimize the beamforming at the BS and IRS without CSI, by minimizing the transmit power, subject to a minimum signal-to-noise ratio (SNR). To solve this problem, a new method based on the Particle Swarm Optimization (PSO) technique is proposed. Results show that the new solution achieves similar performance as that of the optimal beamforming with CSI.

On the Optimal CSI Feedback Rate of Downlink MIMO Systems Using Multiple Receive Antennas in Cellular Networks

A downlink cellular network is considered, in which multiple-antenna base stations (BSs) are distributed following a homogeneous Poisson point process. Each BS serves a single user equipped with multiple-receive antennas. The partial channel state information is achieved at the transmitter using a limited feedback. The singular-value-decomposition-based precoding is performed for the downlink spatial multiplexing. In this letter, the optimal number of feedback bits that maximizes the net spectral efficiency is investigated. The net spectral efficiency is defined to measure the net profit achieved by using limited-feedback-based spatial multiplexing. By extending previous studies, the effect of using multiple-receive antennas on the optimal number is investigated. Specifically, the scaling rate of the optimal number is newly obtained for more than one receive antenna.

Secure multiuser MIMO communication systems with imperfect channel state information

In this paper, we propose a secure wireless communications system through a multiple input multiple output (MIMO) channel which includes a multiple antenna base station and multiple single antenna legitimate users that are overheard by a multiple antenna eavesdropper. By assuming that the eavesdropper’s channel is unknown by the base station, an artificial noise beamforming is used to prevent this eavesdropper to decode legitimate users’ message in the downlink. Additionally, the base station has only imperfect channel state information (CSI) of legitimate users which is the practically relevant case. Under the condition of imperfect CSI, a noise leakage on legitimate users’ signal is occurred and it degrades the achievable average secrecy sum rate. In order to reduce this noise leakage, the semi-orthogonal selection having a rotated codebook is proposed to establish a secure communications link. We demonstrate the average secrecy sum rate results of the proposed algorithm for secure multiuser MIMO systems under imperfect CSI through extensive simulation results.

Precoder Design For Multi-Group Multicasting With a Common Message

This paper considers precoding for multi-group multicasting with a common message. The multiple antenna base station communicates with $K$ clusters, each with $L$ users. There is a common message destined to all users and a private multicast message for each cluster. We study the weighted sum rate (WSR) maximization problem for two different schemes: 1) the base station transmits the superposition of common and multicast messages and 2) the base station concatenates the multicast message vector with the common message. We also formulate a second problem, weighted minimum mean square error (WMMSE) minimization, and prove that WSR maximization and WMMSE minimization are equivalent at the optimal solution. Inspired by the WMMSE problem, we suggest a suboptimal algorithm, based on alternating optimization. We apply this algorithm to the two transmission schemes and understand that there is a fundamental difference between the two. We compare the results with maximal ratio transmission (MRT) and zero-forcing (ZF) precoding and investigate the effects of the number of base station antennas, the number of groups, and the number of users in a group. Finally, we study imperfect successive interference cancellation (SIC) at the receivers and show that the first transmission scheme is more robust.