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Reduced Complexity In-Phase/Quadrature-Phase M-QAM Turbo Equalization Using Iterative Channel Estimation

Reduced Complexity In-Phase/Quadrature-Phase M-QAM Turbo Equalization Using Iterative Channel Estimation
Reduced Complexity In-Phase/Quadrature-Phase M-QAM Turbo Equalization Using Iterative Channel Estimation
A reduced complexity trellis-based turbo equalizer known as the in-phase (I)/quadrature-phase (Q) turbo equalizer (TEQ-IQ) invoking iterative channel impulse response (CIR) estimation is proposed. The underlying principle of TEQ-IQ is based on equalizing the I and Q component of the transmitted signal independently. This requires the equalization of a reduced set of separate I and Q signal components in comparison to all of the possible I/Q phasor combinations considered by the conventional trellis-based equalizer. It was observed that the TEQ-IQ operating in conjunction with iterative CIR estimation was capable of achieving the same performance as the full-complexity conventional turbo equalizer (TEQ-CT) benefiting from perfect CIR information for both 4- and 16-quadrature amplitude modulation (QAM) transmissions, while attaining a complexity reduction factor of 1.1 and 12.2, respectively. For 64-QAM, the TEQ-CT receiver was too complex to be investigated by simulation. However, by assuming that only two turbo equalization iterations were required, which is the lowest possible number of iterations, the complexity of the TEQ-IQ was estimated to be a factor of 51.5 lower than that of the TEQ-CT. Furthermore, at BER = 10-3 the performance of the TEQ-IQ 64-QAM receiver using iterative CIR estimation was only 1.5 dB away from the associated decoding performance curve of the nondispersive Gaussian channel.
Convolutional codes, decoding, in-phase (I), iterative equalization, quadrature-phase (Q), reduced complexity, turbo equalization
2-10
Yeap, B.L.
235ca05f-15be-46ae-952f-604b15dbf849
Wong, C.H.
a69b576c-83a9-478a-b3dd-abac7bbbe7a6
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Yeap, B.L.
235ca05f-15be-46ae-952f-604b15dbf849
Wong, C.H.
a69b576c-83a9-478a-b3dd-abac7bbbe7a6
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1

Yeap, B.L., Wong, C.H. and Hanzo, L. (2003) Reduced Complexity In-Phase/Quadrature-Phase M-QAM Turbo Equalization Using Iterative Channel Estimation. IEEE Transactions on Wireless Communications, 2 (1), 2-10.

Record type: Article

Abstract

A reduced complexity trellis-based turbo equalizer known as the in-phase (I)/quadrature-phase (Q) turbo equalizer (TEQ-IQ) invoking iterative channel impulse response (CIR) estimation is proposed. The underlying principle of TEQ-IQ is based on equalizing the I and Q component of the transmitted signal independently. This requires the equalization of a reduced set of separate I and Q signal components in comparison to all of the possible I/Q phasor combinations considered by the conventional trellis-based equalizer. It was observed that the TEQ-IQ operating in conjunction with iterative CIR estimation was capable of achieving the same performance as the full-complexity conventional turbo equalizer (TEQ-CT) benefiting from perfect CIR information for both 4- and 16-quadrature amplitude modulation (QAM) transmissions, while attaining a complexity reduction factor of 1.1 and 12.2, respectively. For 64-QAM, the TEQ-CT receiver was too complex to be investigated by simulation. However, by assuming that only two turbo equalization iterations were required, which is the lowest possible number of iterations, the complexity of the TEQ-IQ was estimated to be a factor of 51.5 lower than that of the TEQ-CT. Furthermore, at BER = 10-3 the performance of the TEQ-IQ 64-QAM receiver using iterative CIR estimation was only 1.5 dB away from the associated decoding performance curve of the nondispersive Gaussian channel.

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More information

Published date: January 2003
Keywords: Convolutional codes, decoding, in-phase (I), iterative equalization, quadrature-phase (Q), reduced complexity, turbo equalization
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 258302
URI: http://eprints.soton.ac.uk/id/eprint/258302
PURE UUID: c3e8e48c-158f-43a9-851e-a648ba1d8450
ORCID for L. Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 30 Sep 2003
Last modified: 03 Dec 2019 02:06

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