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A particle swarm algorithm for symbols detection in wideband spatial multiplexing systems

Published: 07 July 2007 Publication History

Abstract

This paper explores the application of the particle swarm algorithm for a NP-hard problem in the area of wireless communications. The specific problem is of detecting symbols in a Multi-Input Multi-Output (MIMO) communications system. This approach is particularly attractive as PSO is well suited for physically realizable, real-time applications, where low complexity and fast convergence is of absolute importance. While an optimal Maximum Likelihood (ML) detection using an exhaustive search method is prohibitively complex, we show that the Swarm Intelligence (SI) optimized MIMO detection algorithm gives near-optimal Bit Error Rate (BER) performance in fewer iterations, thereby reducing the ML computational complexity significantly. The simulation results suggest that the proposed detector gives an acceptable performance complexity trade-off in comparison with ML and VBLAST detector.

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      cover image ACM Conferences
      GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
      July 2007
      2313 pages
      ISBN:9781595936974
      DOI:10.1145/1276958
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      Published: 07 July 2007

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      Author Tags

      1. PSO
      2. multi-input multi output systems
      3. symbol detection

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      GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
      Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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      View all
      • (2021)Swarm intelligence for next-generation networksJournal of Network and Computer Applications10.1016/j.jnca.2021.103141191:COnline publication date: 1-Oct-2021
      • (2021)Optimality of Linear MIMO Detection for 5G Systems via 1-Opt Local SearchJournal of Electrical Engineering & Technology10.1007/s42835-020-00625-0Online publication date: 8-Feb-2021
      • (2021)MIMO Systems in Wireless Communications: State of the ArtInformation and Communication Technology for Competitive Strategies (ICTCS 2020)10.1007/978-981-16-0882-7_103(1141-1153)Online publication date: 6-Jul-2021
      • (2018)Mutation-Based Bee Colony Optimization Algorithm for Near-ML Detection in GSM-MIMOAdvances in Signal Processing and Communication10.1007/978-981-13-2553-3_13(125-135)Online publication date: 20-Nov-2018
      • (2018)DE/PSO‐aided hybrid linear detectors for MIMO‐OFDM systems under correlated arraysTransactions on Emerging Telecommunications Technologies10.1002/ett.349529:12Online publication date: 12-Dec-2018
      • (2017)A Weighted Combining Algorithm for Spatial Multiplexing MIMO DF Relaying SystemsIEEE Transactions on Communications10.1109/TCOMM.2017.273654965:11(4751-4764)Online publication date: Nov-2017
      • (2017)A robust MIMO detection algorithm using gravitationally co-ordinated swarm2017 Conference on Information and Communication Technology (CICT)10.1109/INFOCOMTECH.2017.8340612(1-6)Online publication date: Nov-2017
      • (2017)A near-ML performance hybrid dijkstra and firefly algorithm for large MIMO detection2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT.2017.8204114(1-6)Online publication date: Jul-2017
      • (2017)Social spider optimizer based large MIMO detector2017 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)10.1109/ANTS.2017.8384183(1-6)Online publication date: Dec-2017
      • (2016)A low-complexity hybrid algorithm based on particle swarm and ant colony optimization for large-MIMO detectionExpert Systems with Applications: An International Journal10.1016/j.eswa.2015.12.00850:C(66-74)Online publication date: 15-May-2016
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