Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems With Partial CSIT: A Rate-Splitting Approach

By Hamdi Joudeh, Bruno Clerckx. IEEE Transactions on Communications, 2016

412 citations recorded by the source corpus.

This paper considers the sum-rate (SR) maximization problem in downlink multi-user multiple input simgle output (MU-MISO) systems under imperfect channel state information at the transmitter (CSIT). Contrary to existing works, we consider a rather unorthodox transmission scheme. In particular, the message intended to one of the users is split into two parts: a common part which can be recovered by all users, and a private part recovered by the corresponding user. On the other hand, the rest of users receive their information through private messages. This rate-splitting (RS) approach was shown to boost the achievable degrees of freedom when CSIT errors decay with increased SNR. In this paper, the RS strategy is married with linear precoder design and optimization techniques to achieve a maximized ergodic SR (ESR) performance over the entire range of SNRs. Precoders are designed based on partial CSIT knowledge by solving a stochastic rate optimization problem using means of sample average approximation coupled with the weighted minimum mean square error approach. Numerical results show that in addition to the ESR gains, the benefits of RS also include relaxed CSIT quality requirements and enhanced achievable rate regions compared with conventional transmission with no rate-splitting.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/50b8fb03b155b4b6ff356dff28e6ade89b158547

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Citations in the corpus

Coded Federated Computing in Wireless Networks with Straggling Devices and Imperfect CSI (2019, positive): “We also demonstrated the advantages of a superposition-coding based scheme in the presence of imperfect CSI [18].”
Rate-Splitting Multiple Access: Fundamentals, Survey, and Future Research Trends (2022, methodology): “Surprisingly, the sum-DoF achieved by RS was shown in [28] to match the DoF upper bound obtained in [102].”
Rate-Splitting Unifying SDMA, OMA, NOMA, and Multicasting in MISO Broadcast Channel: A Simple Two-User Rate Analysis (2019, methodology): “Results highlight that RS provides signiﬁcant beneﬁts in terms of spectral efﬁciency [3], [6], [7], [9], [13]–[15], energy efﬁciency [4], robustness [8], and CSI feedback overhead reduction [6], [12] over conventional strategies used in LTE-A/5G that rely on fully treating interference as noise…”
Fundamentals of Wireless Information and Power Transfer: From RF Energy Harvester Models to Signal and System Designs (2018, background): “…strategy has been shown to outperform conventional linear precoding in a wide range of network loads (underloaded and overloaded regimes) and user deployments (with a diversity of channel directions, channel strengths and qualities of Channel State Information at the Transmitter) [139], [140].”
A Primer on Rate-Splitting Multiple Access: Tutorial, Myths, and Frequently Asked Questions (2022, methodology): “of RSMA discovered in recent years [9], [18], [19], [67].”
Rate splitting for MIMO wireless networks: a promising PHY-layer strategy for LTE evolution (2016, background): “.6 Further details on RS precoders optimization can be found in [8] for the sum-rate maximization and in [9] for the minimum rate maximization subject to a total transmit power constraint, and the power minimization under rate constraints.”