Tree-Search Multiple-Symbol Differential Decoding for Unitary Space-Time Modulation

Pauli, Volker; Lampe, Lutz

doi:10.1109/tcomm.2007.902500

Cited by 38 publications

(42 citation statements)

References 27 publications

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“…e.g. [30]- [32]. A straightforward adaptation of MSDD to multicarrier transmission is to apply a 1D observation window which extends either in time or in frequency depending on the direction of differential encoding.…”

Section: Multiple-symbol Differential Detection (Msdd)mentioning

confidence: 99%

“…With the ML-MSDD metric in the form of (23) efficient tree-search algorithms devised for single-carrier DSTM and 1D MSDD in [32,42,43] can now be readily applied to DSFM and 2D MSDD.…”

Section: B Tree-search Algorithms For 2d Msddmentioning

confidence: 99%

“…Various variants of tree-search algorithms applicable to solve (23) have been discussed and compared in [32], including those of [42,43]. For the sake of brevity, we do not repeat the description of these algorithms, but only mention those variants particularly suited for MSDD and considered for performance discussion in Section VI.…”

Section: Implementation Aspects 1) Tree-search Algorithmsmentioning

confidence: 99%

“…In order to break the exponential complexity of ML-MSDD with increasing observation window size, we develop a representation of the detection problem that is amenable to lowcomplexity or "fast" optimal and suboptimal tree-search methods. In this context, we borrow from [32] and adapt tree-search detection methods originally developed for single-carrier DSTM to DSFM considered here. Finally, we provide expressions for the symbol-error rate (SER) of 2D ML-MSDD for DSFM under spatially correlated fading, which enable a quick and accurate performance evaluation, and we illustrate the efficacy of our approach by means of numerical examples.…”

Section: Introductionmentioning

confidence: 99%

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Differential Space-Frequency Modulation and Fast 2-D Multiple-Symbol Differential Detection for MIMO-OFDM

Pauli

Lampe

Huber

2008

IEEE Trans. Veh. Technol.

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The combination of differential space-frequency modulation (DSFM) with orthogonal frequency division multiplexing (OFDM) is attractive for transmission over time-and frequency-selective multiple-input multiple-output (MIMO) channels and detection without the need for channel state information (CSI) at the receiver. It is well known that simple differential detection results in a high error floor already for moderate time and frequency selectivity of the channel. More sophisticated multiple-symbol differential detection (MSDD), which jointly processes multiple received symbols, overcomes this limitation, usually at the price of higher detection complexity. In this paper we consider DSFM for MIMO-OFDM transmission and MSDD at the receiver. Inspired by previous work presented in the literature, we devise a novel DSFM scheme, which makes use of spatial and/or spectral (multipath) diversity and is particularly suited for MIMO-OFDM and power-efficient, low-delay MSDD. We further investigate the application of a two-dimensional (2D) observation window to MSDD (2D-MSDD) in order to exploit channel correlations in both time and frequency direction. We develop a representation of the detection problem that is amenable to tree-search decoding, whose application leads to a tremendous reduction in MSDD complexity or "fast" MSDD. An analytical approximation of the symbol-error rate of 2D-MSDD for MIMO-OFDM under spatially correlated fading is derived, which enables quick and accurate performance evaluations. Numerical and simulation results corroborate the efficacy of our approach and show that power efficiency close to that of coherent detection with perfect CSI is feasible in all standard fading scenarios at reasonable decoder complexity. Index TermsOrthogonal frequency division multiplexing (OFDM), multiple-input multiple-output (MIMO) transmission, differential space-frequency modulation (DSFM), differential space-time modulation (DSTM), multiple-symbol differential detection (MSDD), tree-search decoding, sphere decoding.

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Section: Multiple-symbol Differential Detection (Msdd)mentioning

confidence: 99%

“…With the ML-MSDD metric in the form of (23) efficient tree-search algorithms devised for single-carrier DSTM and 1D MSDD in [32,42,43] can now be readily applied to DSFM and 2D MSDD.…”

Section: B Tree-search Algorithms For 2d Msddmentioning

confidence: 99%

Section: Implementation Aspects 1) Tree-search Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Differential Space-Frequency Modulation and Fast 2-D Multiple-Symbol Differential Detection for MIMO-OFDM

Pauli

Lampe

Huber

2008

IEEE Trans. Veh. Technol.

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“…To circumvent this problem, Multiple-Symbol Differential Decoding (MSDD) was proposed for noncoherent schemes in [12], [13] in order to mitigate the potential performance-erosion at high Doppler frequencies. As a further advance, Multiple-Symbol Differential Sphere Decoding (MSDSD) was introduced in [14], [15] in order to limit the exponentially increasing complexity of MSDD, when increasing the detection window width.…”

Section: Introductionmentioning

confidence: 99%

Multiple-Symbol Differential Sphere Decoding Aided Cooperative Differential Space-Time Spreading for the Asynchronous CDMA Uplink

Ternon

Sugiura

et al. 2011

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

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Abstract-In this paper, we propose a Cooperative Differential SpaceTime Spreading (CDSTS) scheme employing multiple relays, which eliminates the demanding requirement of channel estimation both at the relays and at the destination. More explicitly, the source node employs differential encoding during the first transmission interval, and the multiple relays perform Differential Space-Time Spreading (DSTS) based Amplify-and-Forward (AF) relaying in the second transmission interval. Eliminating high-complexity channel estimation is particularly important at the light-weight shirt-pocket-sized mobile handset based relays, since it is unrealistic to estimate the associated mobile-to-mobile channels, which would also pose a security threat and impose a Doppler-dependent pilot overhead. Finally, it would be prone to a channel-estimation-induced performance degradation, which might be close to the 3 dB non-coherent performance penalty. Loosely Synchronized (LS) CDMA spreading codes were adopted for the asynchronous CDMA uplink for the sake of achieving a near-single-user performance using a low-complexity singleuser matched-filter detector. The potential performance degradation of the noncoherent receiver experienced in fast fading channels is mitigated by the proposed Multiple-Symbol Differential Sphere Decoding (MSDSD).

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2013

Wireless Communications

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Tree-Search Multiple-Symbol Differential Decoding for Unitary Space-Time Modulation

Cited by 38 publications

References 27 publications

Differential Space-Frequency Modulation and Fast 2-D Multiple-Symbol Differential Detection for MIMO-OFDM

Differential Space-Frequency Modulation and Fast 2-D Multiple-Symbol Differential Detection for MIMO-OFDM

Multiple-Symbol Differential Sphere Decoding Aided Cooperative Differential Space-Time Spreading for the Asynchronous CDMA Uplink

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