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  • Open Access

    ARTICLE

    Optimal Hybrid Precoding Based QoE for Partially Structured Massive MIMO System

    Farung Samklang, Peerapong Uthansakul, Monthippa Uthansakul*, Patikorn Anchuen

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1887-1902, 2022, DOI:10.32604/cmc.2022.022139

    Abstract Precoding is a beamforming technique that supports multi-stream transmission in which the RF chain plays a significant role as a digital precoding at the receiver for wireless communication. The traditional precoding contains only digital signal processing and each antenna connects to each RF chain, which provides high transmission efficiency but high cost and hardware complexity. Hybrid precoding is one of the most popular massive multiple input multiple output (MIMO) techniques that can save costs and avoid using complex hardware. At present, network services are currently in focus with a wide range of traffic volumes. In terms of the Quality of… More >

  • Open Access

    ARTICLE

    Energy-Efficient Resource Optimization for Massive MIMO Networks Considering Network Load

    Samira Mujkic1,*, Suad Kasapovic1, Mohammed Abuibaid2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 871-888, 2022, DOI:10.32604/cmc.2022.021441

    Abstract This paper investigates the resource optimization problem for a multi-cell massive multiple-input multiple-output (MIMO) network in which each base station (BS) is equipped with a large number of antennas and each base station (BS) adapts the number of antennas to the daily load profile (DLP). This paper takes into consideration user location distribution (ULD) variation and evaluates its impact on the energy efficiency of load adaptive massive MIMO system. ULD variation is modeled by dividing the cell into two coverage areas with different user densities: boundary focused (BF) and center focused (CF) ULD. All cells are assumed identical in terms… More >

  • Open Access

    ARTICLE

    Massive MIMO Codebook Design Using Gaussian Mixture Model Based Clustering

    S. Markkandan1,*, S. Sivasubramanian2, Jaison Mulerikkal3, Nazeer Shaik4, Beulah Jackson5, Lakshmi Naryanan6

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 361-375, 2022, DOI:10.32604/iasc.2022.021779

    Abstract The codebook design is the most essential core technique in constrained feedback massive multi-input multi-output (MIMO) system communications. MIMO vectors have been generally isotropic or evenly distributed in traditional codebook designs. In this paper, Gaussian mixture model (GMM) based clustering codebook design is proposed, which is inspired by the strong classification and analytical abilities of clustering techniques. Huge quantities of channel state information (CSI) are initially saved as entry data of the clustering process. Further, split into N number of clusters based on the shortest distance. The centroids part of clustering has been utilized for constructing a codebook with statistic… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Decoding and AP Selection for Radio Stripe Network

    Aman Kumar Mishra, Vijayakumar Ponnusamy*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 131-148, 2022, DOI:10.32604/iasc.2022.021017

    Abstract

    Cell-Free massive MIMO (mMIMO) offers promising features such as higher spectral efficiency, higher energy efficiency and superior spatial diversity, which makes it suitable to be adopted in beyond 5G (B5G) networks. However, the original form of Cell-Free massive MIMO requires each AP to be connected to CPU via front haul (front-haul constraints) resulting in huge economic costs and network synchronization issues. Radio Stripe architecture of cell-free mMIMO is one such architecture of cell-free mMIMO which is suitable for practical deployment. In this paper, we propose DNN Based Parallel Decoding in Radio Stripe (DNNBPDRS) to decode the symbols of User Equipments… More >

  • Open Access

    ARTICLE

    Energy Efficiency Trade-off with Spectral Efficiency in MIMO Systems

    Rao Muhammad Asif1, Mustafa Shakir1, Jamel Nebhen2, Ateeq Ur Rehman3, Muhammad Shafiq4,*, Jin-Ghoo Choi4

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5889-5905, 2022, DOI:10.32604/cmc.2022.020777

    Abstract 5G technology can greatly improve spectral efficiency (SE) and throughput of wireless communications. In this regard, multiple input multiple output (MIMO) technology has become the most influential technology using huge antennas and user equipment (UE). However, the use of MIMO in 5G wireless technology will increase circuit power consumption and reduce energy efficiency (EE). In this regard, this article proposes an optimal solution for weighing SE and throughput tradeoff with energy efficiency. The research work is based on the Wyner model of uplink (UL) and downlink (DL) transmission under the multi-cell model scenario. The SE-EE trade-off is carried out by… More >

  • Open Access

    ARTICLE

    Efficient Gauss-Seidel Precoding with Parallel Calculation in Massive MIMO Systems

    Hyun-Sun Hwang1, Jae-Hyun Ro2, Chan-Yeob Park1, Young-Hwan You3, Hyoung-Kyu Song1,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 491-504, 2022, DOI:10.32604/cmc.2022.019397

    Abstract A number of requirements for 5G mobile communication are satisfied by adopting multiple input multiple output (MIMO) systems. The inter user interference (IUI) which is an inevitable problem in MIMO systems becomes controllable when the precoding scheme is used. In this paper, the horizontal Gauss-Seidel (HGS) method is proposed as precoding scheme in massive MIMO systems. In massive MIMO systems, the exact inversion of channel matrix is impractical due to the severe computational complexity. Therefore, the conventional Gauss-Seidel (GS) method is used to approximate the inversion of channel matrix. The GS has good performance by using previous calculation results as… More >

  • Open Access

    ARTICLE

    A Highly Efficient Algorithm for Phased-Array mmWave Massive MIMO Beamforming

    Ayman Abdulhadi Althuwayb1, Fazirulhisyam Hashim2, Jiun Terng Liew2, Imran Khan3, Jeong Woo Lee4, Emmanuel Ampoma Affum5, Abdeldjalil Ouahabi6,7,*, Sébastien Jacques8

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 679-694, 2021, DOI:10.32604/cmc.2021.015421

    Abstract With the rapid development of the mobile internet and the internet of things (IoT), the fifth generation (5G) mobile communication system is seeing explosive growth in data traffic. In addition, low-frequency spectrum resources are becoming increasingly scarce and there is now an urgent need to switch to higher frequency bands. Millimeter wave (mmWave) technology has several outstanding features—it is one of the most well-known 5G technologies and has the capacity to fulfil many of the requirements of future wireless networks. Importantly, it has an abundant resource spectrum, which can significantly increase the communication rate of a mobile communication system. As… More >

  • Open Access

    ARTICLE

    An Enhanced Jacobi Precoder for Downlink Massive MIMO Systems

    Park Chan-Yeob, Hyun-Ro Jae, Jun-Yong Jang, Song Hyoung-Kyu*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 137-148, 2021, DOI:10.32604/cmc.2021.016108

    Abstract Linear precoding methods such as zero-forcing (ZF) are near optimal for downlink massive multi-user multiple input multiple output (MIMO) systems due to their asymptotic channel property. However, as the number of users increases, the computational complexity of obtaining the inverse matrix of the gram matrix increases. For solving the computational complexity problem, this paper proposes an improved Jacobi (JC)-based precoder to improve error performance of the conventional JC in the downlink massive MIMO systems. The conventional JC was studied for solving the high computational complexity of the ZF algorithm and was able to achieve parallel implementation. However, the conventional JC… More >

  • Open Access

    ARTICLE

    Improved Hybrid Beamforming for mmWave Multi-User Massive MIMO

    Ji-Sung Jung1, Won-Seok Lee1, Yeong-Rong Lee1, Jaeho Kim2, Hyoung-Kyu Song1,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3057-3070, 2021, DOI:10.32604/cmc.2021.015673

    Abstract Massive multiple input multiple output (MIMO) has become essential for the increase of capacity as the millimeter-wave (mmWave) communication is considered. Also, hybrid beamforming systems have been studied since full-digital beamforming is impractical due to high cost and power consumption of the radio frequency (RF) chains. This paper proposes a hybrid beamforming scheme to improve the spectral efficiency for multi-user MIMO (MU-MIMO) systems. In a frequency selective fading environment, hybrid beamforming schemes suffer from performance degradation since the analog precoder performs the same precoding for all subcarriers. To mitigate performance degradation, this paper uses the average channel covariance matrix for… More >

  • Open Access

    ARTICLE

    Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems

    Adeeb Salh1, Lukman Audah1,*, Qazwan Abdullah1, Nor Shahida M. Shah2, Shipun A. Hamzah1, Shahilah Nordin3, Nabil Farah2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3189-3214, 2021, DOI:10.32604/cmc.2021.014746

    Abstract Energy efficiency (EE) is a critical design when taking into account circuit power consumption (CPC) in fifth-generation cellular networks. These problems arise because of the increasing number of antennas in massive multiple-input multiple-output (MIMO) systems, attributable to inter-cell interference for channel state information. Apart from that, a higher number of radio frequency (RF) chains at the base station and active users consume more power due to the processing activities in digital-to-analogue converters and power amplifiers. Therefore, antenna selection, user selection, optimal transmission power, and pilot reuse power are important aspects in improving energy efficiency in massive MIMO systems. This work… More >

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