Performance comparison of MRT and ZF for single cell downlink massive MIMO system

Mohammad, Mohammad A. B.; Osman, Abdalla A.; Elhag, Nihad A. A.

doi:10.1109/iccneee.2015.7381427

Cited by 11 publications

(10 citation statements)

References 6 publications

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“…n is additive white Gaussian noise vector at the users. Then, the received signal by the k th user after using the linear precoding is [10].…”

Section: Massive Mimo Communication Technologymentioning

confidence: 99%

“…where √ p d h k w k s k is the desired signal for user k and K i=1,i̸ =k √ p d h k w i s i is the multi-user interference signal. The signal to interference plus noise ratio (SINR) of user k is given by [10]…”

Section: Massive Mimo Communication Technologymentioning

confidence: 99%

“…Inserting ( 8) and ( 9) into (10), the energy efficiency of a downlink massive MIMO system is given by…”

Section: Ee =mentioning

confidence: 99%

“…The massive MIMO linear precoding techniques' precoding matrix (W) is summarized below [8]- [10], [23], [42]:…”

Section: B Linear Precoding Techniquesmentioning

confidence: 99%

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Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

et al. 2022

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Massive MIMO and mmWave communication are the technologies for achieving 5G design goals. Fortunately, these two technologies share a symbiotic integration. As a result, amalgamating mmWave communications with massive MIMO forms, "mmWave-massive MIMO," which significantly improves spectral and energy efficiency. It also achieves high multiplexing gains and increases mobile network capacity. However, massive MIMO, mmWave communications, and mmWave-massive MIMO systems have been studied independently. Consequently, this article explores the ideas, performances, comparisons, and discussions of these three 5G technologies jointly, considering their precoding and beamforming methods. On the other hand, the complexity of these technologies increases when a large number of antennas and radio frequencies (RFs) are used. Thus, several investigations are going on to search for the appropriate precoding and beamforming strategies with low cost, power, and complexity. Therefore, massive MIMO linear precoding techniques such as zero-forcing, maximum ratio transmission, regularized zero-forcing, truncated polynomial expansion and phased zero forcing are addressed in this work. In addition, the most common non-linear precoding schemes: dirty-paper coding, Tomlinson-Harashima, and vector perturbation, are presented. Furthermore, a detailed discussion of the beamforming techniques called analog, digital, and hybrid analog-digital beamforming schemes is included. We also examine the potential of hybrid analog-digital beamforming with its fully-connected and sub-connected architecture approaches in making mmWave massive MIMO a reality. We evaluate their performance with the parameters: bit error rate, signal to noise ratio, complexity, spectral efficiency, and energy efficiency. According to the analytical and simulation results, the partially-connected hybrid analog/digital beamforming architecture offers better allover performance for mmWave-Massive MIMO communications by compromising: power consumption, cost, complexity, and performance. Finally, the potential future directions in mmWave-massive MIMO precoding and beamforming challenges are addressed.

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“…n is additive white Gaussian noise vector at the users. Then, the received signal by the k th user after using the linear precoding is [10].…”

Section: Massive Mimo Communication Technologymentioning

confidence: 99%

Section: Massive Mimo Communication Technologymentioning

confidence: 99%

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Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

et al. 2022

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“…The signal received by the k th user after using the linear precoding scheme is given by x = Ws which is the precoded signal at the BS, s ∈ C K×1 is the information bearing signal with E{ss H } = I K , W ∈ C M ×K is the precoding matrix at the BS and p d is the downlink transmit power for user k. n is AWGN (additive white Gaussian noise) vector at the users with unit variance and mean zero elements. Then, signal received by the k th user after using the linear precoding scheme is given by [26]…”

Section: Massive Mimo System Modelmentioning

confidence: 99%

Massive MIMO, mmWave and mmWave-Massive MIMO Communications: Performance Assessment with Beamforming Techniques

Engda¹,

Wondie²,

Steinbrunn³

2020

Preprint

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A considerable amount of enabling technologies are being explored in the era of fifth generation (5G) mobile system. The dream is to build a wireless network that substantially improves the existing mobile networks in all performance metrics. To address this 5G design targets, massive MIMO (multiple input multiple output) and mmWave (millimeter wave) communication are also candidate technologies. Luckily, in many respects these two technologies share a symbiotic integration. Accordingly, a logical step is to integrate mmWave communications and massive MIMO to form mmWave-massive MIMO which substantially increases user throughput, improve spectral and energy efficiencies, increase the capacity of mobile networks and achieve high multiplexing gains. Thus, this work analyses the concepts, performances, comparison and discussion of these technologies called: massive MIMO, mmWave Communications and mmWave-massive MIMO systems jointly. Besides, outcomes of extensive researches, emerging trends together with their respective benefits, challenges, proposed solutions and their comparative analysis is addressed. The performance of hybrid analog-digital beamforming architecture with a fully digital and analog beamforming techniques are also analyzed. Analytical and simulation results show that the low-complexity hybrid analog-digital precoding achieves all round comparable precoding gains for mmWave-Massive MIMO technology.

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Joint Evaluation of Spectral Efficiency, Energy Efficiency and Transmission Reliability in Massive MIMO Systems

Kebede

Kassaw

Wondie

et al. 2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Performance comparison of MRT and ZF for single cell downlink massive MIMO system

Cited by 11 publications

References 6 publications

Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

Massive MIMO, mmWave and mmWave-Massive MIMO Communications: Performance Assessment with Beamforming Techniques

Joint Evaluation of Spectral Efficiency, Energy Efficiency and Transmission Reliability in Massive MIMO Systems

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