Related papers: Deep-Learning-based Millimeter-Wave Massive MIMO f…
Efficient resource allocation with hybrid precoder design is essential for massive MIMO systems operating in millimeter wave (mmW) domain. Owing to a higher energy efficiency and a lower complexity of a partially connected hybrid…
In broadband millimeter-wave (mm-Wave) systems, it is desirable to design hybrid beamformers with common analog beamformer for the entire band while employing different baseband beamformers in different frequency sub-bands. Furthermore, the…
Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates thanks to the large bandwidth available at mmWave frequencies. To realize sufficient link margin, mmWave systems will employ directional beamforming with…
Hybrid beamforming is key to achieving energy-efficient 5G wireless networks equipped with massive amount of antennas. Low-resolution data converters bring yet another degree of freedom to energy efficiency for the state-of-the-art 5G…
Millimeter-wave and terahertz technologies have been attracting attention from the wireless research community since they can offer large underutilized bandwidths which can enable the support of ultra-high-speed connections in future…
Hybrid analog-digital signal processing (HSP) is an enabling technology to harvest the potential of millimeter-wave (mmWave) massive-MIMO communications. In this paper, we present a general deep learning (DL) framework for efficient design…
The deployment of millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems cannot rely solely on digital precoding due to hardware constraints. Instead, hybrid precoding, which combines digital and radio frequency (RF)…
Hybrid precoder and combiner designs are conceived for decentralized parameter estimation in millimeter wave (mmWave) multiple-input multiple-output (MIMO) wireless sensor networks (WSNs). More explicitly, efficient pre- and post-processing…
In this letter, we aim to design a robust hybrid precoder and combiner against beam misalignment in millimeter-wave (mmWave) communication systems. We consider the inclusion of the `error statistics' into the precoder and combiner design,…
We propose a deep-learning approach for the joint MIMO detection and channel decoding problem. Conventional MIMO receivers adopt a model-based approach for MIMO detection and channel decoding in linear or iterative manners. However, due to…
Massive multiple-input multiple-output (MIMO) is a key technology for 5G wireless communications with a promise of significant capacity increase. The use of low-resolution data converters is crucial for massive MIMO to make the overall…
Massive multiple-input multiple-output (mMIMO) technology has transformed wireless communication by enhancing spectral efficiency and network capacity. This paper proposes a novel deep learning-based mMIMO precoder to tackle the complexity…
Hybrid precoding is a cost-effective approach to support directional transmissions for millimeter wave (mmWave) communications. While existing works on hybrid precoding mainly focus on single-user single-carrier transmission, in practice…
Milimeter wave (mmWave) band mobile communications can be a solution to the continuously increasing traffic demand in modern wireless systems. Even though mmWave bands are scarcely occupied, the design of a prospect transceiver should…
Full-duplex millimeter wave (mmWave) communication has shown increasing promise for self-interference cancellation via hybrid precoding and combining. This paper proposes a novel mmWave multiple-input multiple-output (MIMO) design for…
Massive multiple-input multiple-output (MIMO) is a key technology for emerging next-generation wireless systems. Utilizing large antenna arrays at base-stations, massive MIMO enables substantial spatial multiplexing gains by simultaneously…
Analog/digital hybrid precoder and combiner have been widely used in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems due to its energy-efficient and economic superiorities. Infinite resolution of phase shifters (PSs)…
Millimeter wave (mmWave) is a key technology for fifth-generation (5G) and beyond communications. Hybrid beamforming has been proposed for large-scale antenna systems in mmWave communications. Existing hybrid beamforming designs based on…
In this letter, we investigate the hybrid beamforming for millimeter wave massive multiple-input multiple-output (MIMO) system based on deep reinforcement learning (DRL). Imperfect channel state information (CSI) is assumed to be available…
Millimeter wave (mmWave) communications has been regarded as a key enabling technology for 5G networks. In contrast to conventional multiple-input-multiple-output (MIMO) systems, precoding in mmWave MIMO cannot be performed entirely at…