MMSE-Based Precoding for Rate Splitting Systems With Finite Feedback

Lu, Guangyan; Li, Lihua; Tian, Hui; Qian, Feng

doi:10.1109/lcomm.2017.2785221

Cited by 39 publications

(31 citation statements)

References 11 publications

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“…Some optimize the sum rate [15], while others focus on the pre-log factor at high SNR [16]- [18]. MMSE precoder has also been considered in previous works but is only limited for private messages [19], [20]. In this work, we are interested in the unanswered, yet fundamental, question of whether the RS scheme can be close to optimal in a stronger sense than the DoF even with perfect CSIT (which can be regarded as an extreme case of the imperfect CSIT).…”

Section: Introductionmentioning

confidence: 99%

On Linearly Precoded Rate Splitting for Gaussian MIMO Broadcast Channels

Yang

Shamai

2021

IEEE Trans. Inform. Theory

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In this paper, we consider a general K-user Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). We assume that the channel state is deterministic and known to all the nodes. While the private-message capacity region is well known to be achievable with dirty paper coding (DPC), we are interested in the simpler linearly precoded transmission schemes. In particular, we focus on linear precoding schemes combined with rate-splitting (RS). First, we derive an achievable rate region with minimum mean square error (MMSE) precoding at the transmitter and joint decoding of the sub-messages at the receivers. Then, we study the achievable sum rate of this scheme and obtain two findings: 1) an analytically tractable upper bound on the sum rate that is shown numerically to be a close approximation, and 2) how to reduce the number of active streams -crucial to the overall complexity -while preserving the sum rate to within a constant loss. The latter results in two practical algorithms: a stream elimination algorithm and a stream ordering algorithm. Finally, we investigate the constant-gap optimality of linearly precoded RS with respect to the capacity. Our result reveals that, while the achievable rate of linear precoding alone can be arbitrarily far from the capacity, the introduction of RS can help achieve the capacity region to within a constant gap in the two-user case. Nevertheless, we prove that the RS scheme's constant-gap optimality does not extend to the three-user case. Specifically, we show, through a pathological example, that the gap between the sum rate and the sum capacity can be unbounded.

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Section: Introductionmentioning

confidence: 99%

On Linearly Precoded Rate Splitting for Gaussian MIMO Broadcast Channels

Yang

Shamai

2021

IEEE Trans. Inform. Theory

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“…Not only the sum-rate maximization criterion has been considered but also a max-min fairness approach has been presented in [22], where overloaded multigroup multicasting scenarios where also considered. In [23] RS was proposed for a system with random vector quantization feedback. In [24,25], RS with common stream combining techniques was developed to exploit multiple antennas at the receiver and improve the overall sum-rate performance.…”

Section: Introductionmentioning

confidence: 99%

Rate-Splitting Meets Cell-Free MIMO Communications

Flores¹,

Lamare²,

Mishra³

2021

Preprint

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Multiuser multiple-input multiple-output wireless communications systems have the potential to satisfy the performance requirements of fifth-generation and future wireless networks. In this context, cell-free (CF) systems, where the antennas are distributed over the area of interest, have attracted attention because of their potential to enhance the overall efficiency and throughput performance when compared to traditional networks based on cells. However, the performance of CF systems is degraded by imperfect channel state information (CSI). To mitigate the detrimental effects of imperfect CSI, we employ rate splitting (RS) -a multiple-access scheme. The RS approach divides the messages of the users into two separate common and private portions so that interference is managed robustly. Unlike prior works, where the impact of RS in CF systems remains unexamined, we propose a CF architecture that employs RS with linear precoders to address deteriorated CSI. We derive closed-form expressions to compute the sum-rate performance of the proposed RS-CF architecture. Our numerical experiments show that our RS-CF system outperforms existing systems in terms of sum-rate, obtaining up to 10% higher gain.

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“…Linear precoding techniques with RS have been explored in [8], where the sum rate performance with partial CSIT is maximized. In [9,10] the effects of the imperfect CSIT caused by finite feedback are mitigated. RS with receivers equipped with multiple antennas is considered in [11] In contrast, non-linear precoders, such as the Tomlinson-Harashima precoder (THP), have been considered in [12].…”

Section: Introductionmentioning

confidence: 99%

Multi-Branch Tomlinson-Harashima Precoding for Rate Splitting Based Systems with Multiple Antennas

Flores

Lamare

Clerckx

2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Rate splitting (RS) has emerged as a valuable technology for wireless communications systems due to its capability to deal with uncertainties in the channel state information at the transmitter (CSIT). RS with linear and non-linear precoders, such as the Tomlinson-Harashima (THP) precoder, have been explored in the downlink (DL) of multiuser multi antenna systems. In this work, we propose a multi-branch (MB) scheme for a RS-based multiple-antenna system, which creates patterns to order the transmitted symbols and enhances the overall sum rate performance compared to existing approaches. Analytical expressions to describe the signal-to-interference-plusnoise ratio (SINR) and compute the sum rate are derived. Simulation results show that the proposed MB-THP for RS outperforms conventional THP and MB-THP schemes.

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MMSE-Based Precoding for Rate Splitting Systems With Finite Feedback

Cited by 39 publications

References 11 publications

On Linearly Precoded Rate Splitting for Gaussian MIMO Broadcast Channels

On Linearly Precoded Rate Splitting for Gaussian MIMO Broadcast Channels

Rate-Splitting Meets Cell-Free MIMO Communications

Multi-Branch Tomlinson-Harashima Precoding for Rate Splitting Based Systems with Multiple Antennas

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