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Multiuser MIMO-OFDM for Next-Generation Wireless Systems

Multiuser MIMO-OFDM for Next-Generation Wireless Systems
Multiuser MIMO-OFDM for Next-Generation Wireless Systems
This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems.
0018-9219
1430-1469
Jiang, M
64b09206-9d05-4fa3-9749-81ea8bb5347c
Hanzo, L
66e7266f-3066-4fc0-8391-e000acce71a1
Jiang, M
64b09206-9d05-4fa3-9749-81ea8bb5347c
Hanzo, L
66e7266f-3066-4fc0-8391-e000acce71a1

Jiang, M and Hanzo, L (2007) Multiuser MIMO-OFDM for Next-Generation Wireless Systems. Proceedings of the IEEE, 95 (7), 1430-1469.

Record type: Article

Abstract

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems.

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Published date: July 2007
Additional Information: Invited Paper
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 264571
URI: http://eprints.soton.ac.uk/id/eprint/264571
ISSN: 0018-9219
PURE UUID: 6a693c60-6fc3-426d-b6e4-cc641ec7e214
ORCID for L Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 23 Sep 2007
Last modified: 17 Dec 2019 02:03

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Contributors

Author: M Jiang
Author: L Hanzo ORCID iD

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