Worst-case weighted sum-rate maximization in multicell massive MIMO downlink system for 5G communications

Chinnadurai, Sunil; Selvaprabhu, Poongundran; Jiang, Xueqin; Hai, Han; Lee, Moon Ho

doi:10.1016/j.phycom.2018.01.006

Cited by 13 publications

(5 citation statements)

References 38 publications

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“…The WSR problem in this study is solved as a weighted sum minimum mean square error-problem with optimized mean square error-weights. The robust beam forming approach has been used in [25] to calculate the WSR for a multi-cell massive MIMO downlink system. In [4], the authors have investigated achievable data rate of a hybrid system comprising of cascaded PLC/VLC system in coexistence with the RF system for a constrained transmit power.…”

Section: C1v C2vmentioning

confidence: 99%

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Optimisation of indoor hybrid PLC/VLC/RF communication systems

et al. 2020

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In this work, we propose a hybrid power line communication (PLC)/visible light communication (VLC)/radio frequency (RF) fronthaul with a fiber based wired backhaul system to support massive number of smart devices (SDs). Since, a signal-to-noise ratio (SNR) based access point (AP) association and bandwidth (BW) allocation for each SD do not necessarily improve the system capacity, we propose novel and efficient AP association and BW allocation strategies to maximize the sum rate capacity (SRC) of the hybrid system under consideration. An optimization problem is formulated for the SRC with the AP association and BW allocation as the optimization parameters and a hierarchical decomposition method is used to convert the non-linear optimization problem into a set of convex optimization problems. Then, the proposed strategies are used to solve the optimization problem in an iterative manner till the SRC converges to an optimal value. Further, an analytical approximation for the BW allocated to each SD for a given AP association is derived using the Lagrangian multiplier method. The performance of the proposed system is evaluated through extensive numerical results. Moreover, the effect of the increased number of SDs on the optimal SRC is analysed.

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Section: C1v C2vmentioning

confidence: 99%

“…The constraint in (23) upper bound the BW available with each AP, respectively. The constraint in (24) ensures that the allocated BW to an SD has to be non-negative. The optimisation problem in (21) is a non-linear programming problem with association and BW allocation as the optimisation parameters [43].…”

Section: Problem Formulationmentioning

confidence: 99%

Optimisation of indoor hybrid PLC/VLC/RF communication systems

et al. 2020

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“…The 5G cellular networks are being implemented with the specific goal of serving a very diverse service mix, each with its own set of specifications. Massive multiple input multiple output (mMIMO) (Ghosh and Chopra, 2019; Azizipour et al , 2019; Chinnadurai et al , 2018; Liao et al , 2019) is one among them, which is considered as a very challenging theory, developed for enhancing the wireless network’s performance, which integrates the imminent 5G technology. It manages a large number of controllable antennas at the base station (BS), resulting in greater energy and spectral efficiency improvements.…”

Section: Introductionmentioning

confidence: 99%

Enhanced optimization assisted interference mitigation with vertical beamforming in 3D MIMO-OFDMA for 5G wireless communication network

Yadav

Tripathi

2021

IJPCC

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Purpose Multiple input multiple-output (MIMO) has emerged as one among the many noteworthy technologies in recent wireless applications because of its powerful ability to improve bandwidth efficiency and performance, i.e. through developing its unique spatial multiplexing capability and spatial diversity gain. For carrying out an enhanced communication in next-generation networks, the MIMO and orthogonal frequency division multiple systems were combined that facilitate the spatial multiplexing on resource blocks (RBs) based on time-frequency. This paper aims to propose a novel approach for maximizing the throughput of cell-edge users and cell-center users. Design/methodology/approach In this work, the specified multi-objective function is defined as the single objective function, which is solved by the introduction of a new improved algorithm as well. This optimization problem can be resolved by the fine-tuning of certain parameters such as assigned power for RB, cell-center user, cell-edge user and RB allocation. The fine-tuning of parameters is attained by a new improved Lion algorithm (LA), termed as Lion with new cub generation (LA-NCG) model. Finally, the betterment of the presented approach is validated over the existing models in terms of signal to interference plus noise ratio, throughput and so on. Findings On examining the outputs, the adopted LA-NCG model for 4BS was 66.67%, 66.67% and 20% superior to existing joint processing coordinated multiple point-based dual decomposition method (JC-DDM), fractional programming (FP) and LA models. In addition, the throughput of conventional JC-DDM, FP and LA models lie at a range of 10, 45 and 35, respectively, at the 100th iteration. However, the presented LA-NCG scheme accomplishes a higher throughput of 58. Similarly, the throughput of the adopted scheme observed for 8BS was 59.68%, 44.19% and 9.68% superior to existing JC-DDM, FP and LA models. Thus, the enhancement of the adopted LA-NCG model has been validated effectively from the attained outcomes. Originality/value This paper adopts the latest optimization algorithm called LA-NCG to establish a novel approach for maximizing the throughput of cell-edge users and cell-center users. This is the first that work uses LA-NCG-based optimization that assists in fine-tuning certain parameters such as assigned power for RB, cell-center user, cell-edge user and RB allocation.

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“…In order to combat multiple frequency offsets, the literature [9][10][11] adopts the equalization method to eliminate the frequency offset, but the performance of this method will degradate with increasing the offset frequency. In [4], a frequency offset correction algorithm for distributed transmit antenna MIMO OFDM is proposed, to improve the performance of the equalization-based frequency offset elimination method, which corrects multiple frequency offsets before equalization and reduces the interference caused by frequency offset [12][13][14][15]. The lower limit of the conditional average signal to interference and noise ratio (SINR, Signal-Interference-Noise-Ratio) of the subcarriers on the antenna is the criterion correction frequency offset, but it has two disadvantages.…”

Section: Introductionmentioning

confidence: 99%

Minimize MIMO OFDM interference and noise ratio using polynomial-time algorithm

Husein¹

2020

IJECE

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In the distributed transmit antenna MIMO OFDM system, each transmitting antenna has different frequency offset between each transmitting antenna and receiver due to the use of independent crystal oscillator. This paper proposes Polynomial-time algorithm for correcting the frequency offset in a received signal by maximizing the conditional average signal. The algorithm focus on reducing to interference and noise ratio of each subcarrier on the receiving antenna by frequency offset. The simulation result shows the performance of the proposed algorithm is slightly improved compared with the existing frequency offset correction algorithm, and the complexity is reduced by 50% or more.

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Worst-case weighted sum-rate maximization in multicell massive MIMO downlink system for 5G communications

Cited by 13 publications

References 38 publications

Optimisation of indoor hybrid PLC/VLC/RF communication systems

Optimisation of indoor hybrid PLC/VLC/RF communication systems

Enhanced optimization assisted interference mitigation with vertical beamforming in 3D MIMO-OFDMA for 5G wireless communication network

Minimize MIMO OFDM interference and noise ratio using polynomial-time algorithm

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