Prospect of the VLSI Architecture for Massive MIMO Detection

Liu, Leibo; Peng, Guiqiang; Wei, Shaojun

doi:10.1007/978-981-13-6362-7_7

Cited by 3 publications

(6 citation statements)

References 17 publications

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“…Linear detectors use linear operations such as matrix inversion, multiplication, or projection to perform signal detection with low complexity and high parallelism, but they suffer from performance degradation due to noise enhancement, interference, or channel ill-conditioning [15]. Well-known detectors, such as matched-filter (MF) receivers, zeroforcing (ZF) receivers, and minimum mean-square-error (MMSE) receivers can asymptotically achieve capacity as the number of antennas at the BS is large enough compared to the number of users and the channel vectors from different users are independent [7].…”

Section: Signal Detectionmentioning

confidence: 99%

Overview of Interference Management in Massive Multiple- Input Multiple-Output Systems for 5G Networks

Aikoun,

Yin

2024

Preprint

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New challenges have arisen in the field of wireless communication systems since the advent of Fifth Generation (5G) networks and the main objectives of delivering higher data rates, ultra-low latency, more reliability, and massive network capacity. While massive multiple-input multiple-output (MIMO) systems have emerged as a key technology for delivering a more uniform user experience to multiple users simultaneously, the deployment of multiple radiated elements in a confined area can lead to interference between the transmitted and received signals, resulting in the degradation of system efficiency. Therefore, interference management techniques are essential to mitigate this impact and enhance system performance. This review aims to explore interference management techniques in massive MIMO systems, including beamforming methods, non-orthogonal multiple access (NOMA), and joint transmission coordinated multi-point (JT-CoMP). The objective is to analyze the performance of these techniques in terms of the network capacity, coverage, and reliability and to compare their effectiveness in reducing interference. The valuable insights gained from this investigation will serve to inform the design and optimization of these systems.

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Section: Signal Detectionmentioning

confidence: 99%

Overview of Interference Management in Massive Multiple- Input Multiple-Output Systems for 5G Networks

Aikoun,

Yin

2024

Preprint

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“…These features render massive MIMO scalable with respect to the number of base station antennas, M [6] (pp. [10][11][12][13][14][15].…”

Section: Massive Mimo Systemsmentioning

confidence: 99%

Interference Management in Massive MIMO System for 5G Networks: A survey

Aikoun,

Yin

2023

Preprint

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The advent of 5th Generation (5G) networks have created new challenges for wireless communication systems due to the increasing demand for high data rates, low latency, and ubiquitous connectivity. Massive Multiple-Input Multiple-Output (MIMO) systems have emerged as one of the key technologies for 5G networks, which can support multiple users simultaneously and improve system capacity and coverage. However, the use of multiple antennas in the same area to serve very large number of users can generate interference between transmitted signals, which can degrade the received signals as well as the system efficiency. Therefore, interference management techniques are essential in massive MIMO systems to reduce the impact of interference and improve system performance. This research aims to investigate interference management techniques in massive MIMO systems including beamforming method, non-orthogonal multiple access (NOMA), and joint transmission coordinated multi-point (JT-CoMP). The objective is to analyze the performance of these techniques in terms of system capacity, coverage, and reliability and compare their effectiveness in reducing interference. The research findings will provide valuable insights into the most effective interference management techniques for 5G networks and inform the design and optimization of the systems.

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“…Figure 5 shows the dependencies of FER from SNR for the MU-MIMO-Uplink system. It is well known that to maximize the efficiency of overloaded systems, it is obligatory to use optimal, or close to optimal, MIMO detectors [ 12 ]. For overload systems, the question of computational complexity is the first one.…”

Section: Simulation Of Mu-siso and Mu-mimo Uplink System In Overload ...mentioning

confidence: 99%

“…The load factor also can be used for the analysis single-user mode MIMO (Single User MIMO-SU-MIMO) and for multiuser mode MIMO (Multiuser MIMO-MU-MIMO) systems as well as for NOMA systems [ 12 ]. It is shown in [ 8 ] that MIMO channel can be represented as a combination of orthogonal channels, i.e., orthogonal resources, with different characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…Theoretical analysis of the MIMO channel has shown that the best results are obtained when the number of receiving antennas at the base station

is greater or equal to the total number of multiplexed data streams of all users, which is usually equal to the total number of transmitting antennas of all users

[ 6 , 11 , 12 , 13 , 14 , 15 , 16 ]. This conclusion has been originally obtained for a single user system [ 8 ], where it is shown that when the condition

is met, the system bandwidth increases linearly from the number of transmitting antennas.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Uplink NOMA-MIMO Systems with Rayleigh Power Distribution

Бакулин

Rejeb

Kreyndelin

et al. 2022

Sensors

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The article is devoted to multiple-input multiple-output antenna systems, also called MIMO systems, which are widely used in wireless communication systems. In this article we consider a case when the MIMO system works in overloaded mode. In this mode MIMO systems can be considered as a system with non-orthogonal multiple access NOMA. The main goal of this article is to analyze this interesting case using statistical computer simulation. Based on the analysis of the capacity of a discrete-continuous multiuser MIMO uplink channel, the possibility of such systems functioning in overload mode is proved.

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Prospect of the VLSI Architecture for Massive MIMO Detection

Cited by 3 publications

References 17 publications

Overview of Interference Management in Massive Multiple- Input Multiple-Output Systems for 5G Networks

Overview of Interference Management in Massive Multiple- Input Multiple-Output Systems for 5G Networks

Interference Management in Massive MIMO System for 5G Networks: A survey

Uplink NOMA-MIMO Systems with Rayleigh Power Distribution

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