On the Performance of FDD Cell-Free Massive MIMO with Compressed Sensing Channel Estimation

Han, Tongzhou; Zhao, Dixian

doi:10.1109/icct52962.2021.9658057

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…As such, FDD should be considered for the implementation of CF-mMIMO systems. Currently, few works consider FDD-based CF-mMIMO systems [91,92,[106][107][108][109].…”

Section: Fddmentioning

confidence: 99%

A Survey of NOMA-Aided Cell-Free Massive MIMO Systems

Apiyo,

Izydorczyk

2024

Electronics

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The Internet of Everything is leading to an increasingly connected intelligent digital world. Envisaged sixth-generation wireless networks require new solutions and technologies due to stringent network requirements. The benefits of cell-free massive MIMO (CF-mMIMO) and non-orthogonal multiple access (NOMA) have brought substantial attention to these approaches as potential technologies for future networks. In CF-mMIMO, numerous distributed access points are linked to a central processing unit, which allocates the same time-frequency resources to a smaller group of users. On the other hand, NOMA can support more users than its orthogonal counterparts by utilizing non-orthogonal resource allocation. This paper provides a comprehensive review and survey of NOMA-aided CF-mMIMO (CF-mMIMO-NOMA). Specifically, we present a comprehensive review of massive MIMO, CF-mMIMO, and NOMA. We then present a state-of-the-art research review of CF-mMIMO-NOMA. Finally, we discuss the challenges and potential of combining CF-mMIMO-NOMA with other enabling technologies to enhance performance.

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“…As such, FDD should be considered for the implementation of CF-mMIMO systems. Currently, few works consider FDD-based CF-mMIMO systems [91,92,[106][107][108][109].…”

Section: Fddmentioning

confidence: 99%

A Survey of NOMA-Aided Cell-Free Massive MIMO Systems

Apiyo,

Izydorczyk

2024

Electronics

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“…To this end, several research works have investigated the downlink CSI estimation in FDD MMIMO systems, thereby taking into account the spatial correlation at the BS; see, e.g, [20][21][22][23][24][25][26][27][28]. Another area of study has been on CSI estimation utilizing methods based on compressed sensing (CS) [29][30][31][32][33][34]. In addition, a further advancement in CSI estimation is the application of hybrid two-stage precoding techniques in FDD MMIMO systems [35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Maximizing the Downlink Data Rates in Massive Multiple Input Multiple Output with Frequency Division Duplex Transmission Mode Using Power Allocation Optimization Method with Limited Coherence Time

Naser,

Salman,

Alsabah

2024

Telecom

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The expected development of the future generation of wireless communications systems such as 6G aims to achieve an ultrareliable and low-latency communications (URLLCs) while maximizing the data rates. These requirements push research into developing new advanced technologies. To this end, massive multiple input multiple output (MMIMO) is introduced as a promising transmission approach to fulfill these requirements. However, maximizing the downlink-achievable sum rate (DASR) in MMIMO with a frequency division duplex (FDD) transmission mode and limited coherence time (LCT) is very challenging. To address this challenge, this paper proposes a DASR maximization approach using a feasible power allocation optimization method. The proposed approach is based on smartly allocating the total transmit power between the data transmission and training sequence transmission for channel estimation. This can be achieved by allocating more energy to the training signal than the data transmission during the channel estimation process to improve the quality of channel estimation without compromising more training sequence length, thus maximizing the DASR. Additionally, the theory of random matrix approach is exploited to derive an asymptotic closed-form expression for the DASR with a regularized zero-forcing precoder (RZFP), which allows the power optimization process to be achieved without the need for computationally complex Monte Carlo simulations. The results provided in this paper indicate that a considerable enhancement in the DASR performance is achieved using the proposed power allocation method in comparison with the conventional uniform power allocation method.

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“…These BSs jointly transmit the signals coherently to serve the users without cell boundaries, thus significantly improving spectral efficiency [ 5 ]. To further improve the performance of CF networks, various solutions such as beamforming [ 6 ], power allocation [ 7 ], and channel estimation [ 8 ] have been proposed. Nevertheless, deploying a large number of BSs to cover a certain area requires a significant cost and power consumption that restricts the cellular vendors to deploy several BSs at a large scale.…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity Beamforming Design for a Cooperative Reconfigurable Intelligent Surface-Aided Cell-Free Network

Siddiqi

Munir

Mohsan

et al. 2023

Sensors

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Cell-free (CF) networks are proposed to suppress the interference among collocated cells by deploying several BSs without cell boundaries. Nevertheless, as installing several base stations (BSs) may require high power consumption, cooperative CF networks integrated with a reconfigurable intelligent surface (RIS)/metasurface can avoid this problem. In such cooperative RIS-aided MIMO networks, efficient beamforming schemes are essential to boost their spectral and energy efficiency. However, most of the existing available beamforming schemes to maximize spectral and energy efficiency are complex and entail high complexity due to the matrix inversions. To this end, in this work we present a computationally efficient stochastic optimization-based particle swarm optimization (PSO) algorithm to amplify the spectral efficiency of the cooperative RIS-aided CF MIMO system. In the proposed PSO algorithm, several swarms are generated, while the direction of each swarm is tuned in each iteration based on the sum-rate performance to obtain the best solution. Our simulation results show that our proposed scheme can approximate the performance of the existing solutions for both the performance metrics, i.e., spectral and energy efficiency, at a very low complexity.

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On the Performance of FDD Cell-Free Massive MIMO with Compressed Sensing Channel Estimation

Cited by 4 publications

References 10 publications

A Survey of NOMA-Aided Cell-Free Massive MIMO Systems

A Survey of NOMA-Aided Cell-Free Massive MIMO Systems

Maximizing the Downlink Data Rates in Massive Multiple Input Multiple Output with Frequency Division Duplex Transmission Mode Using Power Allocation Optimization Method with Limited Coherence Time

Low-Complexity Beamforming Design for a Cooperative Reconfigurable Intelligent Surface-Aided Cell-Free Network

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