Scalable and Adaptable Diversity/Multiplexing Trade-Off in a Multi-User Massive-MIMO Environment

Bergaoui, Halima; Mlayah, Yosra; Tlili, Fethi; Rouissi, Fatma

doi:10.1109/scc47175.2019.9116100

Cited by 4 publications

(5 citation statements)

References 8 publications

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“…Diversity refers to using multi-antennas to transmit duplicate versions of the data. Diversity can increase the reliability of detection and improve the quality of the wireless link [160]. Concurrently, spatial multiplexing focuses on increasing the throughput and spectral efficiency so that different data streams can be sent independently [161].…”

Section: ) Diversity and Spatial Multiplexing In Mimomentioning

confidence: 99%

See 1 more Smart Citation

Integration of Hybrid Networks, AI, Ultra Massive-MIMO, THz Frequency, and FBMC Modulation Toward 6G Requirements: A Review

Alhaj,

Jamlos,

Manap

et al. 2024

IEEE Access

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The fifth-generation (5G) wireless communications have been deployed in many countries with the following features: wireless networks at 20 Gbps as peak data rate, a latency of 1 ms, reliability of 99.999%, maximum mobility of 500 km/h, a bandwidth of 1 GHz, and a capacity of 10 6 up to Mbps/m 2 . Nonetheless, the rapid growth of applications, such as extended/virtual reality (XR/VR), online gaming, telemedicine, cloud computing, smart cities, the Internet of Everything (IoE), and others, demand lower latency, higher data rates, ubiquitous coverage, and better reliability. These higher requirements are the main problems that have challenged 5G while concurrently encouraging researchers and practitioners to introduce viable solutions. In this review paper, the sixth-generation (6G) technology could solve the 5G limitations, achieve higher requirements, and support future applications. The integration of multiple access techniques, terahertz (THz), visible light communications (VLC), ultra-massive multiple-input multiple-output (um-MIMO), hybrid networks, cell-free massive MIMO, and artificial intelligence (AI)/machine learning (ML) have been proposed for 6G. The main contributions of this paper are a comprehensive review of the 6G vision, KPIs (key performance indicators), and advanced potential technologies proposed with operation principles. Besides, this paper reviewed multiple access and modulation techniques, concentrating on Filter-Bank Multicarrier (FBMC) as a potential technology for 6G. This paper ends by discussing potential applications with challenges and lessons identified from prior studies to pave the path for future research.

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Section: ) Diversity and Spatial Multiplexing In Mimomentioning

confidence: 99%

“…Depending on the channel condition, the embedded switching technique can shift between spatial and diversity multiplexing for each cluster of two data streams. This method reduces the system's bit error rate without sacrificing the data rate [160].…”

Section: ) Diversity and Spatial Multiplexing In Mimomentioning

confidence: 99%

Integration of Hybrid Networks, AI, Ultra Massive-MIMO, THz Frequency, and FBMC Modulation Toward 6G Requirements: A Review

Alhaj,

Jamlos,

Manap

et al. 2024

IEEE Access

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show abstract

“…One of the most important massive MIMO techniques is the spatial multiplexing. Spatial multiplexing consists of sending different data streams independently in order to offer higher peak throughput 14,15 . Spatial multiplexing is also called MIMO transmission, which reflects that the channels in spatial multiplexing have multiple inputs and outputs, that can be used for uplink and downlink transmissions 16 .…”

Section: Introductionmentioning

confidence: 99%

“…Spatial multiplexing consists of sending different data streams independently in order to offer higher peak throughput. 14,15 Spatial multiplexing is also called MIMO transmission, which reflects that the channels in spatial multiplexing have multiple inputs and outputs, that can be used for uplink and downlink transmissions. 16 There are two types of MIMO, namely, single-user MIMO (SU-MIMO) and multiuser MIMO (MU-MIMO).…”

Section: Introductionmentioning

confidence: 99%

Massive multi‐in multi‐out multiuser multiplexing based on transmission mode 3

Zeng

Ouyang

2021

Int J Communication

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Summary Multiuser multi‐in multi‐out (MU‐MIMO) technology using the fifth generation mobile network (5G) massive antenna can greatly increase the existing network capacity and help address problems related to large increases in network traffic. In this study, massive MIMO multiuser space division multiplexing based on transmission mode 3 (TM3) is realized by dividing massive MIMO antenna into virtual beam and fan section. Then the performance evaluations on the MU‐MIMO system in practical existing networks were conducted. The results showed that this technology can realize three times the amount of spatial multiplexing while still maintaining good mobility performance in a no‐load network. In addition, the capacity of the cell can be increased by the massive MIMO system in an existing network for a large user population (for a space division multiplexing factor of approximately 1.83). Test results are used to prove the effectiveness of the frequency‐division duplex massive MIMO multiuser multiplexing based on TM3 to increase the capacity of an existing network.

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“…Also, the deployment of the embedded switching between Alamouti STBC and ZF spatial multiplexing according to the instantaneous channel state in a multi‐user massive MIMO context is investigated in Bergaoui et al 23 However, to the best of our knowledge, the transmission for massive MIMO‐NOMA and STBC systems has not been well studied.…”

Section: Introductionmentioning

confidence: 99%

Multiple‐access interference suppression in massive multiple‐input multiple‐output‐non‐orthogonal multiple access based on space–time block coding

Akbarian

Ghazi‐Maghrebi

2021

Int J Communication

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Non-orthogonal multiple-access (NOMA) scheme using massive multipleinput multiple-output (MIMO) transmission suffers from interference between users. In this paper, we propose a novel MIMO-NOMA framework based on space-time block code (STBC) to decrease the multiple-access interference (MAI), when the number of users is increasing. In this paper, besides giving an analysis of network, cluster, group, and users, we first present the system model. Then, an efficient precoder and detector are designed based on interference analysis. In particular, the proposed scheme can decompose a massive MIMO-NOMA system into multiple separated single-input single-output NOMA channels. Also, analytical results are developed to evaluate the performance of the system. To address the dramatic increment of power level, with the aid of the proposed algorithm, the optimal solution is achieved. Mathematical analyses for both MIMO-NOMA and STBC are presented to design efficient precoding and detection. Finally, simulation results, based on STBC, are provided to verify the theoretical analysis to demonstrate significant capacity improvements of the massive MIMO-NOMA. K E Y W O R D Smultiple-input multiple-output (MIMO), non-orthogonal multiple access (NOMA), precoding design, space-time block code (STBC)

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Scalable and Adaptable Diversity/Multiplexing Trade-Off in a Multi-User Massive-MIMO Environment

Cited by 4 publications

References 8 publications

Integration of Hybrid Networks, AI, Ultra Massive-MIMO, THz Frequency, and FBMC Modulation Toward 6G Requirements: A Review

Integration of Hybrid Networks, AI, Ultra Massive-MIMO, THz Frequency, and FBMC Modulation Toward 6G Requirements: A Review

Massive multi‐in multi‐out multiuser multiplexing based on transmission mode 3

Multiple‐access interference suppression in massive multiple‐input multiple‐output‐non‐orthogonal multiple access based on space–time block coding

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