Effective Coding Gain for Space-Time Codes

Chui, Jimmy; Calderbank, A.R.

doi:10.1109/isit.2006.261844

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…Theorem 2.2: (Transmit-alphabet constrained, rate-diversity tradeoff for flat-fading channels) [35], [43] If a constellation of size is used for transmission and the diversity order of the system is , then the rate that can be achieved is bounded as (7) in bits per transmission.…”

Section: B Tradeoff Between Rate and Reliabilitymentioning

confidence: 99%

“…Linear additive codeword designs are amenable to computationally-efficient lattice decoding strategies, such as the sphere decoder [9] and appear to be less susceptible to degradation in performance at low-to-moderate SNR caused by the number of nearest neighbors [7]. With this motivation, choosing the transmitted signal to be additive of the following form (21) allows the composite code to be linear in the complex field as well.…”

Section: A Linear Code Constructions: Flat-fading Channelsmentioning

confidence: 99%

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Diversity Embedded Codes: Theory and Practice

Dusad

Diggavi

Al-Dhahir³

et al. 2008

IEEE J. Sel. Top. Signal Process.

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Abstract-Diversity embedded codes are high-rate space-time codes that have a high-diversity code embedded within them. They allow a form of communication where the high-rate code opportunistically takes advantage of good channel realizations while the embedded high-diversity code provides guarantees that at least part of the information is received reliably. Over the past few years, code designs and fundamental limits of performance for such codes have been developed. In this paper, we review these ideas by giving the developments in a unified framework. In particular, we present both the coding technique as well as information-theoretic bounds in the context of Intersymbol Interference (ISI) channels. We investigate the systems implications of diversity embedded codes by examining value to network utility maximization, unequal error protection for wireless transmission, rate opportunism and packet delay optimization.

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Section: B Tradeoff Between Rate and Reliabilitymentioning

confidence: 99%