On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm

Downlink joint processing (JP) between base stations eliminates the inter-cell interference in a cellular system with a frequency reuse factor of one and improves the spectral efficiency of cell-edge users. JP has a huge impact on both feedback and backhaul load, and thus partial JP was presented to...

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Main Authors: Faisal, Ali Raed, Hashim, Fazirulhisyam, Ismail, Mahamod, Noordin, Nor Kamariah
Format: Conference or Workshop Item
Language:English
Published: IEEE 2015
Online Access:http://psasir.upm.edu.my/id/eprint/56041/
http://psasir.upm.edu.my/id/eprint/56041/1/On%20spectral%20efficiency%20maximization%20in%20a%20partial%20joint%20processing%20system%20using%20a%20multi-start%20particle%20swarm%20optimization%20algorithm.pdf
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author Faisal, Ali Raed
Hashim, Fazirulhisyam
Ismail, Mahamod
Noordin, Nor Kamariah
author_facet Faisal, Ali Raed
Hashim, Fazirulhisyam
Ismail, Mahamod
Noordin, Nor Kamariah
author_sort Faisal, Ali Raed
building UPM Institutional Repository
collection Online Access
description Downlink joint processing (JP) between base stations eliminates the inter-cell interference in a cellular system with a frequency reuse factor of one and improves the spectral efficiency of cell-edge users. JP has a huge impact on both feedback and backhaul load, and thus partial JP was presented to tackle with signaling demand. However, achieving equivalent backhaul reduction based on limited feedback channel state information is challenging when linear techniques, such as zero-forcing beamforming (BF) are used, which led to the use of stochastic algorithms instead. Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). The lack of diversity has been solved in this work by replacing the inactive particles adaptively based on a predefined constant which represents the difference between local best and global best optimization criterion. The performance of the proposed MSPSOA and BPSOA BF is evaluated with respect to full and partial JP using different metrics such as sum-rate, actual interference and convergence using a multipath realistic environment WINNER II channel model. The proposed MSPSOA outperforms BPSOA in terms of average sum-rate by 15.3%, while the actual interference decreased by 14.6% in some conducted scenarios.
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institution Universiti Putra Malaysia
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language English
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spelling upm-560412017-07-03T09:33:09Z http://psasir.upm.edu.my/id/eprint/56041/ On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm Faisal, Ali Raed Hashim, Fazirulhisyam Ismail, Mahamod Noordin, Nor Kamariah Downlink joint processing (JP) between base stations eliminates the inter-cell interference in a cellular system with a frequency reuse factor of one and improves the spectral efficiency of cell-edge users. JP has a huge impact on both feedback and backhaul load, and thus partial JP was presented to tackle with signaling demand. However, achieving equivalent backhaul reduction based on limited feedback channel state information is challenging when linear techniques, such as zero-forcing beamforming (BF) are used, which led to the use of stochastic algorithms instead. Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). The lack of diversity has been solved in this work by replacing the inactive particles adaptively based on a predefined constant which represents the difference between local best and global best optimization criterion. The performance of the proposed MSPSOA and BPSOA BF is evaluated with respect to full and partial JP using different metrics such as sum-rate, actual interference and convergence using a multipath realistic environment WINNER II channel model. The proposed MSPSOA outperforms BPSOA in terms of average sum-rate by 15.3%, while the actual interference decreased by 14.6% in some conducted scenarios. IEEE 2015 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/56041/1/On%20spectral%20efficiency%20maximization%20in%20a%20partial%20joint%20processing%20system%20using%20a%20multi-start%20particle%20swarm%20optimization%20algorithm.pdf Faisal, Ali Raed and Hashim, Fazirulhisyam and Ismail, Mahamod and Noordin, Nor Kamariah (2015) On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm. In: 2015 IEEE 12th Malaysia International Conference on Communications (MICC 2015), 23-25 Nov. 2015, Kuching, Sarawak, Malaysia. (pp. 288-293). 10.1109/MICC.2015.7725449
spellingShingle Faisal, Ali Raed
Hashim, Fazirulhisyam
Ismail, Mahamod
Noordin, Nor Kamariah
On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
title On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
title_full On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
title_fullStr On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
title_full_unstemmed On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
title_short On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
title_sort on spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
url http://psasir.upm.edu.my/id/eprint/56041/
http://psasir.upm.edu.my/id/eprint/56041/
http://psasir.upm.edu.my/id/eprint/56041/1/On%20spectral%20efficiency%20maximization%20in%20a%20partial%20joint%20processing%20system%20using%20a%20multi-start%20particle%20swarm%20optimization%20algorithm.pdf