Multi-antenna Broadcast Channel Research Articles

Cooperative covert communication in multi-antenna broadcast channels

Cooperative covert communication in multi-antenna broadcast channels

Rate-Splitting Multiple Access for Multi-Antenna Downlink Communication Systems: Spectral and Energy Efficiency Tradeoff

Rate-splitting (RS) has recently been recognized as a promising physical-layer technique for multi-antenna broadcast channels (BC). Due to its ability to partially decode the interference and partially treat the remaining interference as noise, RS is an enabler for a powerful multiple access, namely rate-splitting multiple access (RSMA), that has been shown to achieve higher spectral efficiency (SE) and energy efficiency (EE) than both space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) in a wide range of user deployments and network loads. As SE maximization and EE maximization are two conflicting objectives in the moderate and high signal-to-noise ratio (SNR) regimes, the study of the tradeoff between the two criteria is of particular interest. In this work, we address the SE-EE tradeoff by studying the joint SE and EE maximization problem of RSMA in multiple input single output (MISO) BC with rate-dependent circuit power consumption at the transmitter. To tackle the challenges coming from multiple objective functions and rate-dependent circuit power consumption, we first propose two models to transform the original problem into two single-objective problems, namely, weighted-sum method and weighted-power method. A low-complexity algorithm with closed-form solution is proposed to solve each single-objective problem in the two-user system. For the generalized <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> -user system, a successive convex approximation (SCA)-based algorithm is then proposed to optimize the precoders of each transformed problem. Numerical results show that our algorithm converges much faster than existing algorithms. In addition, the performance of RSMA is superior to or equal to SDMA and NOMA in terms of SE, EE and their tradeoff.

Globally Optimal Spectrum- and Energy-Efficient Beamforming for Rate Splitting Multiple Access

Rate splitting multiple access (RSMA) is a promising non-orthogonal transmission strategy for next-generation wireless networks. It has been shown to outperform existing multiple access schemes in terms of spectral and energy efficiency when suboptimal beamforming schemes are employed. In this work, we fill the gap between suboptimal and truly optimal beamforming schemes and conclusively establish the superior spectral and energy efficiency of RSMA. To this end, we propose a successive incumbent transcending (SIT) branch and bound (BB) algorithm to find globally optimal beamforming solutions that maximize the weighted sum rate or energy efficiency of RSMA in Gaussian multiple-input single-output (MISO) broadcast channels. Numerical results show that RSMA exhibits an explicit globally optimal spectral and energy efficiency gain over conventional multi-user linear precoding (MU-LP) and power-domain non-orthogonal multiple access (NOMA). Compared to existing globally optimal beamforming algorithms for MU-LP, the proposed SIT BB not only improves the numerical stability but also achieves faster convergence. Moreover, for the first time, we show that the spectral/energy efficiency of RSMA achieved by suboptimal beamforming schemes (including weighted minimum mean squared error (WMMSE) and successive convex approximation) almost coincides with the corresponding globally optimal performance, making it a valid choice for performance comparisons. The globally optimal results provided in this work are imperative to the ongoing research on RSMA as they serve as benchmarks for existing suboptimal beamforming strategies and those to be developed in multi-antenna broadcast channels.

Cooperative Rate-Splitting for Downlink Multiuser MISO Systems With Partial CSIT

Multiple antenna technology and cooperative relaying are two efficient methods to improve the capacity and reliability of wireless networks. By marrying cooperative relaying with a Rate-Splitting (RS) approach, Cooperative Rate-Splitting (CRS) shows certain benefits compared to several non-cooperative and cooperative schemes in multi-antenna Broadcast Channel (BC). In this paper, we further investigate the CRS with partial Channel State Information at the Transmitter (CSIT), as partial CSIT is an inevitable issue in practical downlink Multi-user Multiple Input Single Output (MU-MISO) systems. The proposed CRS structure includes multiple users, and one user could be selected as a relay to help the other users. With the flexible design, CRS leverages the benefits of user cooperation and relay (or user) selection for cooperative network, and also retains the superiority of RS for multi-antenna BC. Considering the Weighted Average Sum Rate (WASR) performance, we aim to solve the stochastic optimization that jointly involves the precoder design, the time resource allocation, and the relay selection issue. To address the above non-convex problem, a dedicated algorithm for CRS that exploits the Weighted Minimum Mean Square Error (WMMSE) approach and the Convex-Concave Procedure (CCP) is proposed, such that the WASR is maximized by jointly updating the precoding matrix and time allocation factor according to the incoming user channel state estimate. The proposed algorithm then enables us to solve the relay selection through an exhaustive search. Since the optimal relay selection algorithm has a high computational complexity when the number of users is large, we additionally provide a suboptimal heuristic algorithm to strike a balance between complexity and performance. Numerical results demonstrate that the proposed CRS scheme is capable of achieving a larger WASR than its non-cooperative counterpart and several existing beamforming schemes in a wide range of propagation conditions, and the heuristic algorithm achieves a performance close to the optimal one but with lower complexity.

Joint RSMA and IDMA-Based NOMA system for downlink Communication in 5G and Beyond Networks

Future communication networks may encounter various issues in order to facilitate heavy heterogeneous data traffic and large number of users, therefore more advanced multiple access (MA) schemes is required to meet the changing requirements. Recently, a promising physical-layer MA technique has been suggested for multi-antenna broadcast channels, namely Rate Splitting Multiple Access (RSMA). This new scheme has the ability to partially decode the interference and partially treat the remaining interference as noise which makes it to cope with wide range of user deployments and network loads. On the other hand, interleave division multiple access (IDMA) has already been recognized as a potential code domain NOMA (non-orthogonal multiple access) scheme, suitable for 5G and beyond communication network. Hence, in this paper, a new approach of multiple access scheme is proposed to get the grip on new challenges in future communication (6G). The proposed framework consists the joint processing of RSMA and IDMA (code domain NOMA), in which the transmitter involves an IDMA as encoder and allows rate splitting to split the message in two parts i.e. common part and private part, before the actual transmission. The mathematical modeling of proposed system is elaborated in the paper and for simulation purpose the downlink communication scenario has been considered where users faced diverse channel conditions. The weighted sum rate (WSR) performance is evaluated for the proposed scheme which validate the quality of service (QoS) of the joint RS-IDMA system.

Simultaneous wireless information and power transfer optimization via alternating convex-concave procedure with imperfect channel state information

Simultaneous Wireless Information and Power Transfer (SWIPT) systems are viable models to implement wireless charging in Broadcast Channel (BC) systems. With the emergence of Internet of Things (IOT) and the 5th generation of telecommunication systems (5G), to make lifelong powered devices, wireless charging gets wider attention in scientific and industrial community. To optimally design such a system, we optimize a multi-user multi-antenna BC by simultaneously maximizing the sum of harvested energy and minimizing the sum Mean Square Error (MSE) for symbol detection at each receiver node. To have a tractable design problem, we recast this multi-objective problem as a Difference of Convex (DC) bilinear problem. The derived design problem is solved using the Alternating Convex Search (ACS) method and the Penalty Convex-Concave Program (PCCP) procedure. We solve this problem under two conditions: the perfect and the imperfect Channel State Information (CSI). Simulation results prove that the proposed algorithm outperforms reported recent research studies in this field.

Beyond Dirty Paper Coding for Multi-Antenna Broadcast Channel With Partial CSIT: A Rate-Splitting Approach

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

Multi-Antenna Interference Management for Coded Caching

A multi-antenna broadcast channel scenario is considered where a base station delivers contents to cache-enabled user terminals. A joint design of coded caching (CC) and multigroup multicast beamforming is proposed to benefit from spatial multiplexing gain, improved interference management and the global CC gain, simultaneously. The developed general content delivery strategies utilize the multiantenna multicasting opportunities provided by the CC technique while optimally balancing the detrimental impact of both noise and inter-stream interference from coded messages transmitted in parallel. Flexible resource allocation schemes for CC are introduced where the multicast beamformer design and the receiver complexity are controlled by varying the size of the subset of users served during a given time interval, and the overlap among the multicast messages transmitted in parallel, indicated by parameters $\alpha$ and $\beta$, respectively. Degrees of freedom (DoF) analysis is provided showing that the DoF only depends on $\alpha$ while it is independent of $\beta$. The proposed schemes are shown to provide the same degrees-of-freedom at high signal-to-noise ratio (SNR) as the state-of-art methods and, in general, to perform significantly better, especially in the finite SNR regime, than several baseline schemes.

Rate-Splitting Unifying SDMA, OMA, NOMA, and Multicasting in MISO Broadcast Channel: A Simple Two-User Rate Analysis

Considering a two-user multi-antenna Broadcast Channel, this letter shows that linearly precoded Rate-Splitting (RS) with Successive Interference Cancellation (SIC) receivers is a flexible framework for non-orthogonal transmission that generalizes, and subsumes as special cases, four seemingly different strategies, namely Space Division Multiple Access (SDMA) based on linear precoding, Orthogonal Multiple Access (OMA), Non-Orthogonal Multiple Access (NOMA) based on linearly precoded superposition coding with SIC, and physical-layer multicasting. This letter studies the sum-rate and shows analytically how RS unifies, outperforms, and specializes to SDMA, OMA, NOMA, and multicasting as a function of the disparity of the channel strengths and the angle between the user channel directions.

Content Delivery in Erasure Broadcast Channels With Cache and Feedback

We study a content delivery problem in a $K$ -user erasure broadcast channel such that a content providing server wishes to deliver requested files to users, each equipped with a cache of a finite size. Assuming that the transmitter has state feedback and user caches can be filled during off-peak hours reliably by the decentralized content placement, we characterize the achievable rate region as a function of the memory sizes and the erasure probabilities for some special cases. The proposed delivery scheme, based on the broadcasting scheme by Wang and Gatzianas et al., exploits the receiver side information established during the placement phase. Our results can be extended to the centralized content placement as well as multi-antenna broadcast channels with state feedback.

Receiver Cooperation for MIMO Broadcast Channels With Finite-Rate Feedback

Receiver cooperation is an effective technique to improve the performance of multi-antenna Gaussian broadcast channels. In practical systems, the transmitter usually has partial channel state information (CSI) via the finite-rate feedback channel. How could receiver cooperation benefit the system performance in this case? In this letter, we propose a low complexity and effective cooperation scheme based on the principle of decode-and-forward (DF) relaying and successive interference cancelation (SIC) to mitigate the residual multiuser interference. Compared to non-cooperative systems, the proposed scheme brings a twofold benefit: improved chosen space of beamforming vectors and reduced multiuser interference terms. As a result, both degrees-of-freedom gain and power gain can be observed. The degrees-of-freedom gain leads to unbounded throughput with finite feedback rate. The power gain is significant such that the proposed scheme with partial CSI even outperforms the non-cooperative system with perfect CSI in low and moderate signal-to-noise ratio (SNR) region.

Opportunistic interference management: a new approach for multiantenna downlink cellular networks

AbstractA new approach for multiantenna broadcast channels in cellular networks based on multiuser diversity concept is introduced. The technique called opportunistic interference management achieves dirty paper coding capacity asymptotically with minimum feedback required. When there are K antennas at the base station with M mobile users in the cell, the proposed technique only requires K integer numbers related to channel state information between mobile users and base station. The encoding and decoding complexity of this scheme is the same as that of point‐to‐point communications, which makes the implementation of this technique easy. An antenna selection scheme is proposed at the base station to reduce the minimum required mobile users significantly at the expense of reasonable increase in feedback. In order to guarantee fairness, a new algorithm is presented that incorporates opportunistic interference management into existing Global System for Mobile communications (GSM) standard. Copyright © 2014 John Wiley &amp; Sons, Ltd.

MIMO Broadcast Channel with an Unknown Eavesdropper: Secrecy Degrees of Freedom

We study a multi-antenna broadcast channel with two legitimate receivers and an external eavesdropper. We assume that the channel matrix of the eavesdropper is unknown to the legitimate terminals but satisfies a maximum rank constraint. As our main result we characterize the associated secrecy degrees of freedom for the broadcast channel with common and private messages. We show that a direct extension of the single-user wiretap codebook does not achieve the secrecy degrees of freedom. Our proposed optimal scheme involves decomposing the signal space into a common subspace, which can be observed by both receivers, and private subspaces which can be observed by only one of the receivers, and carefully transmitting a subset of messages in each subspace. We also consider the case when each user's private message must additionally remain confidential from the other legitimate receiver and characterize the s.d.o.f.\ region in this case.

Throughput analysis of transmit-nulling SDMA with limited feedback

We recently proposed a precoder codebook for a transmit-nulling space-division multiple access (TN-SDMA) to share spectrum with existing wireless services. Since a portion of the spatial subspaces of a multiantenna broadcast channel is used to eliminate the interference to coexisting systems, TN-SDMA could benefit the efficiency of spectrum usage from the coexistence of different systems in the same band while it always yields lower throughput per unit bandwidth than the orthogonal SDMA (called per user unitary and rate control (PU2RC)) that utilizes all the spatial subspaces for data transmission. This study aims to theoretically quantify the throughput loss of TN-SDMA relative to PU2RC and to analyze the effect of the main system parameters (signal-to-noise ratio (SNR) and the numbers of transmit antennas, users, and feedback bits) on the throughput loss. We derive the theoretical upper bound of the throughput loss of TN-SDMA relative to PU2RC, with the same feedback bits (codebook size). The throughput loss is lower with more transmit antennas, fewer users, lower SNR, or fewer feedback bits. It is interesting to note that the throughput loss converges to an upper limit with an increase in the SNR, which indicates that the SNR has a comparatively minor effect on the throughput loss in the high-SNR region. We also derive the required additional number of feedback bits for TN-SDMA to achieve the throughput of PU2RC (i.e., zero throughput loss). We find that the throughput achieved is feasible at the cost of a practically small number of additional feedback bits.

Product Superposition for MIMO Broadcast Channels

This paper considers the multiantenna broadcast channel without transmit-side channel state information. For this channel, it has been known that when all receivers have channel state information (CSIR), the degrees of freedom (DoFs) cannot be improved beyond what is available via time-division multiple access. The same is true if none of the receivers possess CSIR. This paper shows that an entirely new scenario emerges when receivers have unequal CSIR. In particular, orthogonal transmission is no longer DoF optimal when one receiver has CSIR and the other does not. A multiplicative superposition is proposed for this scenario and shown to attain the optimal DoFs under a wide set of antenna configurations and coherence lengths. Two signaling schemes are constructed based on the multiplicative superposition. In the first method, the messages of the two receivers are carried in the row and column spaces of a matrix, respectively. This method works better than orthogonal transmission while reception at each receiver is still interference-free. The second method uses coherent signaling for the receiver with CSIR, and Grassmannian signaling for the receiver without CSIR. This second method requires interference cancellation at the receiver with CSIR, but achieves higher DoF than the first method.

Regularized Zero-Forcing for Multiantenna Broadcast Channels with User Selection

A multiantenna multiuser broadcast channel with transmitter beamforming and user selection is considered. Different from the conventional works, we consider imperfect channel state information (CSI) which is a practical scenario for multiuser broadcast channels. We propose a robust regularized zero-forcing (RRZF) beamforming at the base station. Then we show that the RRZF outperforms zero-forcing (ZF) and regularized ZF (RZF) beamforming even as the number of users grows to infinity. Simulation results validate the advantage of the proposed robust RZF beamforming.

Sum-Rate Capacity of Random Beamforming for Multi-Antenna Broadcast Channels with Other Cell Interference

In this letter, we analyze the sum rate of random beamforming (RBF) for downlink multi-antenna systems in the presence of other cell interference (OCI). Employing extreme value theory, an expression of the asymptotic ergodic sum rate with a large number of users is derived from the limiting distribution of the sample maximum of the received signal-to-interference-plus-noise ratio. Based on our result, the scaling law of multiuser diversity gain is also exhibited in the context of RBF systems with the OCI, which is shown to coincide with the previous result without the other cell interferers. Simulation results verify the validity of our analysis even with not so large number of users.

Feedback Reduction for CDI-Based Beamforming in the MIMO Broadcast Channel

Recent research has demonstrated that for the multi-antenna broadcast channel, applying transmit precoding based on the channel spatial covariance matrices leads to temporal stability of the achievable network sum rate. This approach allows reduction in the frequency of channel information feedback events at the expense of increased feedback complexity. While recent work has demonstrated the possibility of feedback complexity reduction through matrix decompositions, this paper demonstrates significant additional feedback reduction through compression of the covariance matrices using the Karhunen-Loève Transform.

Opportunistic Random Beamforming with Optimal Precoding for Spatially Correlated Channels

It has been shown recently that dirty paper coding (DPC) achieves optimum sum-rate capacity in a multi-antenna broadcast channel with full channel state (CSI) information at the transmitter. With only partial feedback, random beamforming (RBF) is able to match the sumrate of DPC for large number of users. However, in the presence of spatial correlation, RBF incurs an SNR hit as compared to DPC. In this letter, we explore precoding techniques to reduce the effect of correlation on RBF. We thus derive the optimum precoding matrix that minimizes the rate gap between DPC and RBF. Given the numerical complexity involved in calculating the optimum precoder, we derive approximate precoding matrices that are simple to calculate and close in performance to the optimum precoder.

Fairness maximization and delay analysis for multi-antenna broadcast channels using random beamforming

A Multi-Input Multi-Output (MIMO) broadcast channel with large number ( n) of users is considered. It is assumed each user either receives the minimum rate constraint of R min or remains silent. Accordingly, for the case of random beamforming, an user selection strategy together with a proper power allocation method is proposed, showing the maximum number of active users scales as M log ( log ( n ) ) R min - θ ( 1 ) in the asymptotic case of n → ∞, where M represents the number of transmit antennas. Noting the asymptotic sum-rate capacity of such channel is M log ( log ( n ) ) , the proposed method is able to approach the asymptotic sum-rate capacity within a constant gap. Moreover, it is shown the expected delay of this fair power allocation strategy behaves like R min M n log ( n ) log ( log ( n ) ) - θ ( 1 ) + ω n log ( log ( n ) ) , where the expected delay is defined as the minimum number of channel uses to make sure each user receives at least one packet. Accordingly, it is proved that for sufficiently large ( k) number of channel uses, the average number of services received by a randomly selected user scales as kM log ( log ( n ) ) nR min 1 + O log ( k ) k .