Cooperative Hybrid Transmit Beamforming in Cell-Free mmWave MIMO Networks

Jafri, Meesam; Srivastava, Suraj; Venkategowda, Naveen K. D.; Jagannatham, Aditya K.; Hanzo, Lajos

doi:10.1109/tvt.2022.3229832

“…Moreover, a theoretical analysis on the impact of imperfect state information of beams was presented, from both instantaneous and ergodic aspects, to verify the robustness of the proposed hybrid scheme. Jafri et al [181] developed optimal hybrid beamformers for broadcast, unicast and multicast mmWave CF-mMIMO systems in the presence of interuser/intergroup interference. Moreover, they developed a successive UL hybrid beamforming scheme that maximizes the SINR.…”

Section: A Literature Reviewmentioning

confidence: 99%

Next Generation Multiple Access with Cell-Free Massive MIMO

Mohammadi,

Mobini,

Ngo

et al. 2023

Preprint

0

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<p>To meet the unprecedented mobile traffic demands of future wireless networks, a paradigm shift from conventional cellular networks to distributed communication systems is imperative. Cell-free massive multiple-input multiple-output (CF-mMIMO) represents a practical and scalable embodiment of distributed/network MIMO systems. It inherits not only the key benefits of co-located massive MIMO systems but also the macro-diversity gains from distributed systems. This innovative architecture has demonstrated significant potential in enhancing network performance from various perspectives, outperforming co-located mMIMO and conventional small-cell systems. Moreover, CF-mMIMO offers flexibility in integration with emerging wireless technologies such as full-duplex (FD), non-orthogonal transmission schemes, millimeter-wave (mmWave) communications, ultra-reliable low-latency communication (URLLC), unmanned aerial vehicle (UAV)-aided communication, and reconfigurable intelligent surfaces (RISs). In this paper, we provide an overview of current research efforts on CF-mMIMO systems and their promising future application scenarios. We then elaborate on new requirements for CF-mMIMO networks in the context of these technological breakthroughs. We also present several current open challenges and outline future research directions aimed at fully realizing the potential of CF mMIMO systems in meeting the evolving demands of future wireless networks.</p>

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“…Moreover, a theoretical analysis on the impact of imperfect state information of beams was presented, from both instantaneous and ergodic aspects, to verify the robustness of the proposed hybrid scheme. Jafri et al [181] developed optimal hybrid beamformers for broadcast, unicast and multicast mmWave CF-mMIMO systems in the presence of interuser/intergroup interference. Moreover, they developed a successive UL hybrid beamforming scheme that maximizes the SINR.…”

Section: A Literature Reviewmentioning

confidence: 99%

Next Generation Multiple Access with Cell-Free Massive MIMO

Mohammadi,

Mobini,

Ngo

et al. 2023

Preprint

0

View full text Add to dashboard Cite

<p>To meet the unprecedented mobile traffic demands of future wireless networks, a paradigm shift from conventional cellular networks to distributed communication systems is imperative. Cell-free massive multiple-input multiple-output (CF-mMIMO) represents a practical and scalable embodiment of distributed/network MIMO systems. It inherits not only the key benefits of co-located massive MIMO systems but also the macro-diversity gains from distributed systems. This innovative architecture has demonstrated significant potential in enhancing network performance from various perspectives, outperforming co-located mMIMO and conventional small-cell systems. Moreover, CF-mMIMO offers flexibility in integration with emerging wireless technologies such as full-duplex (FD), non-orthogonal transmission schemes, millimeter-wave (mmWave) communications, ultra-reliable low-latency communication (URLLC), unmanned aerial vehicle (UAV)-aided communication, and reconfigurable intelligent surfaces (RISs). In this paper, we provide an overview of current research efforts on CF-mMIMO systems and their promising future application scenarios. We then elaborate on new requirements for CF-mMIMO networks in the context of these technological breakthroughs. We also present several current open challenges and outline future research directions aimed at fully realizing the potential of CF mMIMO systems in meeting the evolving demands of future wireless networks.</p>

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“…Therefore, 5G uses millimeter wave massive Multiple-Input Multiple-Output (MIMO) to meet user requirements. MIMO will employ antennas in large numbers at the base station and possibly even in user equipment when millimeter wave (mmWave) [ 3 ] bands are used [ 4 ]. MIMO greatly improves the space utilization and improves the throughput of the communication system.…”

Section: Introductionmentioning

confidence: 99%

Wireless Channel Prediction of GRU Based on Experience Replay and Snake Optimizer

Liu

¹

,

Wang

²

,

Sun

³

et al. 2023

Sensors

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Aiming at the problem of poor prediction accuracy of Channel State Information (CSI) caused by fast time-varying channels in wireless communication systems, this paper proposes a gated recurrent network based on experience replay and Snake Optimizer for real-time prediction in real-world non-stationary channels. Firstly, a two-channel prediction model is constructed by gated recurrent unit, which adapts to the real and imaginary parts of CSI. Secondly, we use the Snake Optimizer to find the optimal learning rate and the number of hidden layer elements to build the model. Finally, we utilize the experience pool to store recent historical CSI data for fast learning and complete learning. The simulation results show that, compared with LSTM, BiLSTM, and BiGRU, the gated recurrent network based on experience replay and Snake Optimizer has better performance in the optimization ability and convergence speed. The prediction accuracy of the model is also significantly improved under the dynamic non-stationary environment.

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Cooperative Hybrid Transmit Beamforming in Cell-Free mmWave MIMO Networks

Cited by 13 publications

References 57 publications

Next Generation Multiple Access with Cell-Free Massive MIMO

Next Generation Multiple Access with Cell-Free Massive MIMO

Next Generation Multiple Access with Cell-Free Massive MIMO

Wireless Channel Prediction of GRU Based on Experience Replay and Snake Optimizer

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