An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications

Wang, Dongming; Wei, Hao; You, Xiaohu; Gao, Xiqi; Wang, Jiangzhou

doi:10.1007/s11432-016-0278-5

Cited by 87 publications

(35 citation statements)

References 76 publications

(71 reference statements)

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“…The use of massive antennas was first proposed for multicell multi-user cellular systems in [1] and since then, it has received much research interest [2]- [5]. It was shown that massive multi-input multi-output (MIMO) has very large performance gains compared with the conventional MIMO provided that a sufficiently large number of transmit antennas per active user are employed at each base station (BS).…”

Section: Introductionmentioning

confidence: 99%

Downlink Spectral Efficiency of Distributed Massive MIMO Systems With Linear Beamforming Under Pilot Contamination

Wang

Zhu

et al. 2018

IEEE Trans. Veh. Technol.

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Abstract-In this paper, the downlink spectral efficiency of multi-cell multi-user distributed massive MIMO systems with linear beamforming is studied in the presence of pilot contamination. According to the levels of effective channel gain information at user side, we provide the lower bound and upper bound on user ergodic achievable downlink rate. Due to the different access distance from each user to different remote antenna units, the entries of user channel vectors are no longer identically distributed in distributed massive MIMO systems, which makes the spectral efficiency analysis challenging. Using the properties of Gamma distributions together with the approximate methods for non-isotropic vectors, we derive tractable but accurate closed-form expressions for the rate bounds with maximum ratio transmission (MRT) and zero-forcing (ZF) beamforming in distributed massive MIMO systems. Based on these expressions, user ultimate achievable rates are also given when the ratio of the total number of transmit antennas to the number of users goes to infinity. It is shown that MRT and ZF beamforming achieve the same ultimate rate no matter what levels of effective channel gain information at user side. Numerical results show that ZF achieves better performance gain and faster convergence speed than MRT. When the coherence interval is large, the downlink beamforming training scheme is more preferable for the distributed massive MIMO systems.

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Section: Introductionmentioning

confidence: 99%

Downlink Spectral Efficiency of Distributed Massive MIMO Systems With Linear Beamforming Under Pilot Contamination

Wang

Zhu

et al. 2018

IEEE Trans. Veh. Technol.

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“…For 5G NR scenarios, these problems are more challenging due to the complicated network structures and large number of KPIs. Applications of new features like massive MIMO beamforming [25] are associated with high-dimensional optimization parameters and the optimization problem itself is difficult to model. Also, 5G NR involves multiple KPIs including peak data rate, spectral efficiency, latency, connection density, quality of experience (QoE) and so on.…”

Section: Research Directions For Ai In 5gmentioning

confidence: 99%

AI for 5G: research directions and paradigms

You

Zhang

Tan

et al. 2018

Sci. China Inf. Sci.

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155

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The 5th wireless communication (5G) techniques not only fulfil the requirement of 1, 000 times increase of internet traffic in the next decade, but also offer the underlying technologies to the entire industry and ecology for internet of everything. Compared to the existing mobile communication techniques, 5G techniques are more-widely applicable and the corresponding system design is more complicated. The resurgence of artificial intelligence (AI) techniques offers as an alternative option, which is possibly superior over traditional ideas and performance. Typical and potential research directions to which AI can make promising contributions need to be identified, evaluated, and investigated. To this end, this overview paper first combs through several promising research directions of AI for 5G, based on the understanding of the 5G key techniques. Also, the paper devotes itself in providing design paradigms including 5G network optimization, optimal resource allocation, 5G physical layer unified acceleration, end-to-end physical layer joint optimization, and so on.The 5G technology standards are in development, getting complete and mature [2,3]. In December 2017, 3G Partnership Project (3GPP) officially announced the new standards for 5G New Radio (NR) which include supports for 5G Non-Standalone architecture (NSA) and eMBB [4]. On June 14, 2018, 3GPP formally completed the Standalone (SA) version of the 5G NR standard, marking a long-awaited target date for 5G standardization [5]. These announced standards effectively set the stage to launch full-scale and cost-effective development of 5G networks. Compared to the current 4G networks, 5G NR: (1) enhances the MIMO systems with the massive MIMO technology; (2) makes completion to the time slot structure and resource block (RB) allocation of the orthogonal frequency-division multiplexing (OFDM), proposing a more flexible air interface; (3) will introduce the non-orthogonal multiple access (NOMA) to support the Internet of Things (IoT) in the near future; (4) follows the previous distributed antenna systems [6], splits the wireless functions into distributed units (DU) and central units (CU) and applies network virtualization and network slicing techniques based on cloud computing.Overall, 5G networks will tailor the provisioning mechanisms for more applications and services, hence is more challenging with the complicated configuration issues and evolving service requirements. Before 5G, researches of communication systems mainly aim at satisfactory data transmission rate and supportive mobility management. In the 5G era, the communication systems will gain the abilities to interact with the environment, and the targets are expanded to joint optimizations of ever-increasing numbers of key performance indicators (KPIs) including latency, reliability, connection density, user experience, etc [7]. Meanwhile, new features like the dynamic air interface, virtualised network and network slicing introduce complicated system design and optimization requirements as long as ...

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“…MIMO has become a key technology of many wireless communications standards. By using large-scale antenna arrays at the base station, which is also known as massive MIMO, performance could be further improved [7]- [9]. Massive MIMO has been adopted by the 5G NR standard.…”

Section: Introductionmentioning

confidence: 99%

Performance of High-Mobility MIMO Communications With Doppler Diversity

2020

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Rapid change of the channels in high-speed mobile communications will lead to difficulties in channel estimation and tracking, but can also provide Doppler diversity. In this paper, the performance of multiple-input multiple-output system with pilot-assisted repetitive coding and spatial multiplexing has been studied. With minimum mean square error (MMSE) channel estimation, an equivalent channel model and the corresponding system model are presented. Based on the random matrix theory, the asymptotic expressions of the normalized achievable sum rate of linear receivers, such as maximal ratio combining (MRC) receiver, MMSE detection and MRC-like receiver are derived. In addition, according to the symbol error rate of the MRC-like receiver, the maximum normalized Doppler diversity order, the minimum coding gain loss can be achieved when the repetition number and the signal to noise ratio tend to infinity and corresponding conditions are also derived. Based on the theoretical results, the impacts of different system configurations and channel parameters on system performance have been demonstrated.Index Terms-Doppler diversity, MIMO, deterministic equivalent, high mobility wireless communication system.

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An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications

Cited by 87 publications

References 76 publications

Downlink Spectral Efficiency of Distributed Massive MIMO Systems With Linear Beamforming Under Pilot Contamination

Downlink Spectral Efficiency of Distributed Massive MIMO Systems With Linear Beamforming Under Pilot Contamination

AI for 5G: research directions and paradigms

Performance of High-Mobility MIMO Communications With Doppler Diversity

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