Tomlinson-Harashima Precoded Rate-Splitting With Stream Combiners for MU-MIMO Systems

Flores, André R.; Lamare, Rodrigo C. de; Clerckx, Bruno

doi:10.1109/tcomm.2021.3065145

Cited by 29 publications

(27 citation statements)

References 40 publications

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“…Extensions to other precoders and/or beamforming strategies [30], [28], [29], [31], [32], [33], [34], [35], [37], [38], [36], [44], [40], [39], [41], [42], [43], [45], [46], [47] are possible. Moreover, detection and parameter estimation strategies can also be considered for future work [58], [59], [60], [61], [62], [63], [64], [65], [66], [57], [67].…”

Section: B Cqa-rbd Precodermentioning

confidence: 99%

Study of Linear Precoding and Power Allocation for Large Multiple-Antenna Systems with Coarsely Quantized Signals

Pinto¹,

Lamare²

2021

Preprint

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This work studies coarse quantization-aware BD (CQA−BD) and coarse quantization-aware RBD (CQA−RBD) precoding algorithms for large-scale MU-MIMO systems with coarsely quantized signals and proposes the coarse-quantization most advantageous allocation strategy (CQA−MAAS) power allocation algorithm for linearly-precoded MU-MIMO systems. An analysis of the sum-rate along with studies of computational complexity is also carried out. Finally, comparisons between existing precoding and its power allocated version are followed by conclusions.

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Section: B Cqa-rbd Precodermentioning

confidence: 99%

Study of Linear Precoding and Power Allocation for Large Multiple-Antenna Systems with Coarsely Quantized Signals

Pinto¹,

Lamare²

2021

Preprint

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“…Most of those studies have used alternate optimization assuming perfect channel state information at a transmitter (CSIT). However, in a real environment, it is difficult that a transmitter acquires the estimated channel matrices due to feedback overhead and almost wireless systems use a codebook of precoding matrices for feedback [ 10 , 11 , 12 , 13 ]. In the real systems, wireless transceivers that adopt hybrid beamforming use a protocol for beam management to determine analog beams [ 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Efficient Channel Feedback Scheme for Multi-User MIMO Hybrid Beamforming Systems

Lee

Song

2021

Sensors

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This paper proposes an efficient channel information feedback scheme to reduce the feedback overhead of multi-user multiple-input multiple-output (MU-MIMO) hybrid beamforming systems. As massive machine type communication (mMTC) was considered in the deployments of 5G, a transmitter of the hybrid beamforming system should communicate with multiple devices at the same time. To communicate with multiple devices in the same time and frequency slot, high-dimensional channel information should be used to control interferences between the receivers. Therefore, the feedback overhead for the channels of the devices is impractically high. To reduce the overhead, this paper uses common sparsity of channel and nonlinear quantization. To find a common sparse part of a wide frequency band, the proposed system uses minimum mean squared error orthogonal matching pursuit (MMSE-OMP). After the search of the common sparse basis, sparse vectors of subcarriers are searched by using the basis. The sparse vectors are quantized by a nonlinear codebook that is generated by conditional random vector quantization (RVQ). For the conditional RVQ, the Linde–Buzo–Gray (LBG) algorithm is used in conditional vector space. Typically, elements of sparse vectors are sorted according to magnitude by the OMP algorithm. The proposed quantization scheme considers the property for the conditional RVQ. For feedback, indices of the common sparse basis and the quantized sparse vectors are delivered and the channel is recovered at a transmitter for precoding of MU-MIMO. The simulation results show that the proposed scheme achieves lower MMSE for the recovered channel than that of the linear quantization scheme. Furthermore, the transmitter can adopt analog and digital precoding matrix freely by the recovered channel and achieve higher sum rate than that of conventional codebook-based MU-MIMO precoding schemes.

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“…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. In [26], RS was employed in a single cell along with algorithms to reduce the number of streams and perform successive decoding for large number of users.…”

Section: Introductionmentioning

confidence: 99%

Rate-Splitting Meets Cell-Free MIMO Communications

Flores¹,

Lamare²,

Mishra³

2021

Preprint

Self Cite

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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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Tomlinson-Harashima Precoded Rate-Splitting With Stream Combiners for MU-MIMO Systems

Cited by 29 publications

References 40 publications

Study of Linear Precoding and Power Allocation for Large Multiple-Antenna Systems with Coarsely Quantized Signals

Study of Linear Precoding and Power Allocation for Large Multiple-Antenna Systems with Coarsely Quantized Signals

Efficient Channel Feedback Scheme for Multi-User MIMO Hybrid Beamforming Systems

Rate-Splitting Meets Cell-Free MIMO Communications

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