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Register a new userRate-Splitting Multiple Access to Mitigate the Curse of Mobility in (Massive) MIMO Networks
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Added by
Onur Dizdar
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Rate-Splitting Multiple Access (RSMA) is a flexible and robust multiple access scheme for downlink multi-antenna wireless networks. RSMA relies on multi-antenna Rate-Splitting (RS) at the transmitter and Successive Interference Cancellation (SIC) at the receivers. In this work, we study the performance of RSMA under the practical important setup of imperfect Channel State Information at Transmitter (CSIT) originating from user mobility and latency in the network. First, we derive a lower bound on the ergodic sum-rate of RSMA for an arbitrary number of transmit antennas, number of users, user speeds and transmit power. Then, we study the power allocation between common and private streams and obtain a closed-form solution for the optimal power allocation that maximizes the obtained lower bound. The proposed power allocation greatly reduces precoder design complexity for RSMA. By Link-Level Simulations (LLS), we demonstrate that RSMA with the proposed power allocation is robust to degrading effects of user mobility and has significantly higher performance compared to conventional multi-user (massive) Multiple-Input Multiple-Output (MIMO) strategies. The work has important practical significance as results demonstrate that, in contrast to conventional multi-user (massive) MIMO whose performance collapse under mobility, RSMA can maintain reliable multi-user connectivity in mobile deployments.
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Rate-splitting multiple access (RSMA) has been recognized as a promising physical layer strategy for 6G. Motivated by ever increasing popularity of cache-enabled content delivery in wireless communications, this paper proposes an innovative multigroup multicast transmission scheme based on RSMA for cache-aided cloud-radio access networks (C-RAN). Our proposed scheme not only exploits the properties of content-centric communications and local caching at the base stations (BSs), but also incorporates RSMA to better manage interference in multigroup multicast transmission with statistical channel state information (CSI) known at the central processor (CP) and the BSs. At the RSMA-enabled cloud CP, the message of each multicast group is split into a private and a common part with the former private part being decoded by all users in the respective group and the latter common part being decoded by multiple users from other multicast groups. Common message decoding is done for the purpose of mitigating the interference. In this work, we jointly optimize the clustering of BSs and the precoding with the aim of maximizing the minimum rate among all multicast groups to guarantee fairness serving all groups. The problem is a mixed-integer non-linear stochastic program (MINLSP), which is solved by a practical algorithm we proposed including a heuristic clustering algorithm for assigning a set of BSs to serve each user followed by an efficient iterative algorithm that combines the sample average approximation (SAA) and weighted minimum mean square error (WMMSE) to solve the stochastic non-convex sub-problem of precoder design. Numerical results show the explicit max-min rate gain of our proposed transmission scheme compared to the state-of-the-art trivial interference processing methods. Therefore, we conclude that RSMA is a promising technique for cache-aided C-RAN.
Rate-Splitting Multiple Access (RSMA) is a flexible and robust multiple access scheme for downlink multi-antenna wireless networks. RSMA relies on Rate-Splitting (RS) at the transmitter and Successive Interference Cancellation (SIC) at the receivers. In this work, we study the performance of RSMA in the scenarios related with the important core services of New Radio (NR) and 6G, namely, enhanced Ultra-Reliable and Low-Latency (URLLC) and enhanced Mobile Broadband Communications (eMBB). We present the optimal system designs employing RSMA that target short-packet and low-latency communications as well as robust communications with high-throughput under the practical and important setup of imperfect Channel State Information at Transmitter (CSIT) originating from user mobility and feedback latency in the network. We demonstrate via numerical results that RSMA achieves significantly higher performance than Space Division Multiple Access (SDMA) and Non-Orthogonal Multiple Access (NOMA), and is capable of addressing the requirements for enhanced URLLC and eMBB in 6G efficiently.
In the scalar dirty multiple-access channel, in addition to Gaussian noise, two additive interference signals are present, each known non-causally to a single transmitter. It was shown by Philosof et al. that for strong interferences, an i.i.d. ensemble of codes does not achieve the capacity region. Rather, a structured-codes approach was presented, that was shown to be optimal in the limit of high signal-to-noise ratios, where the sum-capacity is dictated by the minimal (bottleneck) channel gain. In this paper, we consider the multiple-input multiple-output (MIMO) variant of this setting. In order to incorporate structured codes in this case, one can utilize matrix decompositions that transform the channel into effective parallel scalar dirty multiple-access channels. This approach however suffers from a bottleneck effect for each effective scalar channel and therefore the achievable rates strongly depend on the chosen decomposition. It is shown that a recently proposed decomposition, where the diagonals of the effective channel matrices are equal up to a scaling factor, is optimal at high signal-to-noise ratios, under an equal rank assumption. This approach is then extended to any number of transmitters. Finally, an application to physical-layer network coding for the MIMO two-way relay channel is presented.
This work proposes UE selection approaches to mitigate the straggler effect for federated learning (FL) on cell-free massive multiple-input multiple-output networks. To show how these approaches work, we consider a general FL framework with UE sampling, and aim to minimize the FL training time in this framework. Here, training updates are (S1) broadcast to all the selected UEs from a central server, (S2) computed at the UEs sampled from the selected UE set, and (S3) sent back to the central server. The first approach mitigates the straggler effect in both Steps (S1) and (S3), while the second approach only Step (S3). Two optimization problems are then formulated to jointly optimize UE selection, transmit power and data rate. These mixed-integer mixed-timescale stochastic nonconvex problems capture the complex interactions among the training time, the straggler effect, and UE selection. By employing the online successive convex approximation approach, we develop a novel algorithm to solve the formulated problems with proven convergence to the neighbourhood of their stationary points. Numerical results confirm that our UE selection designs significantly reduce the training time over baseline approaches, especially in the networks that experience serious straggler effects due to the moderately low density of access points.
Rate-Splitting Multiple Access (RSMA) has recently appeared as a powerful and robust multiple access and interference management strategy for downlink Multi-user (MU) multi-antenna communications. In this work, we study the precoder design problem for RSMA scheme in downlink MU systems with both perfect and imperfect Channel State Information at the Transmitter (CSIT) and assess the role and benefits of transmitting multiple common streams. Unlike existing works which have considered single-antenna receivers (Multiple-Input Single-Output--MISO), we propose and extend the RSMA framework for multi-antenna receivers (Multiple-Input Multiple-Output--MIMO) and formulate the precoder optimization problem with the aim of maximizing the Weighted Ergodic Sum-Rate (WESR). Precoder optimization is solved using Sample Average Approximation (SAA) together with the proposed vectorization and Weighted Minimum Mean Square Error (WMMSE) based approach. Achievable sum-Degree of Freedom (DoF) of RSMA is derived for the proposed framework as an increasing function of the number of transmitted common and private streams, which is further validated by the Ergodic Sum Rate (ESR) performance using Monte Carlo simulations. Conventional MU-MIMO based on linear precoders and Non-Orthogonal Multiple Access (NOMA) schemes are considered as baselines. Numerical results show that with imperfect CSIT, the sum-DoF and ESR performance of RSMA is superior than that of the two baselines, and is increasing with the number of transmitted common streams. Moreover, by better managing the interference, RSMA not only has significant ESR gains over baseline schemes but is more robust to CSIT inaccuracies, network loads and user deployments.
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