A near-ML performance hybrid dijkstra and firefly algorithm for large MIMO detection

Arijit Datta, Vimal Bhatia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

To meet the ever growing demand of high data rates, employing large number of antennas at the transmitter and receiver is a key feature of future advanced wireless systems. Multiple-input multiple-output (MIMO) systems can provide high data rates with high spectral efficiency and have opened a new gateway in wireless systems. However, design of an efficient, robust and non-erroneous detection algorithm is a huge challenge in MIMO systems. In this paper, a hybrid algorithm has been proposed for large scale MIMO detection. The proposed algorithm is motivated by the popular firefly algorithm and dijkstra's shortest path algorithm. Simulation results reveal that the proposed hybrid algorithm outperforms the conventional zero forcing, minimum mean square error and successive interference cancellation based MIMO detection techniques in terms of bit error rate (BER) performance and achieves near maximum likelihood BER performance. This makes the proposed algorithm an appropriate candidate for reliable detection in large-MIMO systems.

Original languageEnglish
Title of host publication8th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509030385
DOIs
Publication statusPublished - 13-12-2017
Event8th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2017 - Delhi, India
Duration: 03-07-201705-07-2017

Publication series

Name8th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2017

Conference

Conference8th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2017
Country/TerritoryIndia
CityDelhi
Period03-07-1705-07-17

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Modelling and Simulation
  • Artificial Intelligence

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