Appendix B: Introduction to MIMO and Massive MIMO

Deshpande, Swapnaja

doi:10.1002/9781119331797.app2

Cited by 4 publications

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“…On the problem of the estimation of CSI characteristics of the many channels, progress has been made. An examination of energy efficiency aspects is being conducted in addition to the problem of computing cost for precoding schemes [16].…”

Section: Massive Mimo Technologymentioning

confidence: 99%

Survey on Massive MIMO: Technology, Challenges, Opportunities and Benefits

Vaigandla¹,

Venu²

2021

YMER

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Wireless communication technologies have been studied and explored in response to the global shortage of bandwidth in the field of wireless access. Next-generation networks will be enabled by massive MIMO. Using relatively simple processing, it provides high spectral and energy efficiency by combining antennas at the receiver and transmitter. This paper discusses enabling technologies, benefits, and opportunities associated with massive MIMO, and all the fundamental challenges. Global enterprises, research institutions, and universities have focused on researching the 5G mobile communication network. Massive MIMO technologies will utilize simpler and linear algorithms for beam forming and decoding. As part of future 5G, massive MIMO technology will be used to increase the efficiency of spectrum utilization and channel capacity. The paper then summarizes the technologies that are used in massive MIMO system, including channel estimation, pre-coding, and signal detection.

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Section: Massive Mimo Technologymentioning

confidence: 99%

Survey on Massive MIMO: Technology, Challenges, Opportunities and Benefits

Vaigandla¹,

Venu²

2021

YMER

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“…The key idea behind massive‐MIMO is to deploy a large number of antennas at the base station (BS) to serve few‐tens of users. Large number of antennas at the BS provide a twofold improvement over the conventional MIMO systems, ie, it enhances the diversity gain and the multiplexing gain of MIMO systems . Diversity improves reliability of the received symbols at the receiver, whereas spatial multiplexing improves the data rate.…”

Section: Introductionmentioning

confidence: 99%

Reliability feedback–aided low‐complexity detection in uplink massive MIMO systems

Datta

Mandloi

Bhatia

2019

Int J Communication

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Summary Massive multiple‐input multiple‐output (MIMO) plays a crucial role in realizing the demand for higher data rates and improved quality of service for 5G and beyond communication systems. Reliable detection of transmitted information bits from all the users is one of the challenging tasks for practical implementation of massive‐MIMO systems. The conventional linear detectors such as zero forcing (ZF) and minimum mean square error (MMSE) achieve near‐optimal bit error rate (BER) performance. However, ZF and MMSE require large dimensional matrix inversion which induces high computational complexity for symbol detection in such systems. This motivates for devising alternate low‐complexity near‐optimal detection algorithms for uplink massive‐MIMO systems. In this work, we propose an ordered sequential detection algorithm that exploits the concept of reliability feedback for achieving near‐optimal performance in uplink massive‐MIMO systems. In the proposed algorithm, symbol corresponding to each user is detected in an ordered sequence by canceling the interference from all the other users, followed by reliability feedback‐based decision. Incorporation of the sequence ordering and the reliability feedback‐based decision enhances the interference cancellation, which reduces the error propagation in sequential detection, and thus, improves the BER performance. Simulation results show that the proposed algorithm significantly outperforms recently reported massive‐MIMO detection techniques in terms of BER performance. In addition, the computational complexity of the proposed algorithm is substantially lower than that of the existing algorithms for the same BER. This indicates that the proposed algorithm exhibits a desirable trade‐off between the complexity and the performance for massive‐MIMO systems.

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3-D-Printed Wideband Circularly Polarized MIMO Dielectric Resonator Antenna

Yang

2023

IEEE Trans. Antennas Propagat.

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Appendix B: Introduction to MIMO and Massive MIMO

Cited by 4 publications

References 0 publications

Survey on Massive MIMO: Technology, Challenges, Opportunities and Benefits

Survey on Massive MIMO: Technology, Challenges, Opportunities and Benefits

Reliability feedback–aided low‐complexity detection in uplink massive MIMO systems

3-D-Printed Wideband Circularly Polarized MIMO Dielectric Resonator Antenna

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