A BICM-IDD scheme for non-coherent MIMO communication

IEEE Trans. Inform. Theory

Yanıkömeroğlu

2014

Self Cite

Abstract-This paper considers the ergodic noncoherent capacity of a multiple-input multiple-output frequency-flat block Rayleigh fading full duplex relay channel at high signal-to-noise ratios (SNRs). It is shown that, for these SNRs, restricting the input distribution to be isotropic on a compact Grassmann manifold maximizes an upper bound on the cut-set bound. Furthermore, it is shown that, from a degrees of freedom point of view, no relaying is necessary and Grassmannian signalling at the source achieves the upper bound within an SNR-independent gap. When the source-relay channel is sufficiently stronger than the source-destination and relay-destination channels, it is shown that, with the number of relay transmit antennas appropriately chosen, a Grassmannian decode-and-forward scheme, which is devised herein, achieves the ergodic noncoherent capacity of the relay channel within an approximation gap that goes to zero as the SNR goes to infinity. Closed-form expressions for the optimal number of relay transmit antennas indicate that this number decreases monotonically with the source transmit power.Index Terms-Noncoherent communication, decode-andforward relaying, Grassmannian signalling, ergodic capacity.

Section: A Maximizing Imentioning

confidence: 99%

“…The significance of the SNR-independent term increases with the number of receive antennas and decreases with the coherence interval [8], i.e., the time duration during which the channel remains constant. See, e.g., [9] and [10] for comparisons between the performance of coded non-coherent and training-based communication systems.…”

mentioning

confidence: 99%

Grassmannian Signalling Achieves Tight Bounds on the Ergodic High-SNR Capacity of the Noncoherent MIMO Full-Duplex Relay Channel

IEEE Trans. Inform. Theory

Yanıkömeroğlu

2014

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“…In Fig. 6 we provide a comparison between the performance of the quasi-Gray labelling schemes proposed herein with a randomly chosen labelling and the quasi-set-partitioning scheme proposed in [34]. At a BER of 10 −3 , quasi-setpartitioning provides an SNR gain of 0.15 dB over the random labelling.…”

Section: Snr [Db]mentioning

confidence: 99%

Quasi-Gray Labelling for Grassmannian Constellations

Colman

IEEE Trans. Wireless Commun.

El-Azizy

et al. 2011

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This paper presents two polynomial-complexity techniques for assigning Gray-like binary labels to arbitrary Grassmannian constellations. In the first technique, the constellation of interest, , is matched directly to an auxiliary constellation that can be readily Gray labelled. The optimal matching in this technique can be obtained efficiently, but its application is limited to cases in which an auxiliary constellation with a geometric structure that resembles that of can be identified. In the second technique no auxiliary constellation is required and the labels are generated by matching the distance spectrum of with that of a hypothetical constellation that is assumed to be perfectly Gray labelled. Optimal matching in this case is computationally prohibitive. Instead, an efficient suboptimal matching algorithm is proposed. When compared with several existing schemes, the proposed labellings provide better performance in both uncoded and BICM-based non-coherent MIMO systems with iterative demapping and decoding (IDD). Furthermore, with the proposed labels, the Grassmannian-based BICM-IDD scheme performs better than a training-based counterpart that employs the Golden code and optimal demapping. Index Terms-Non-coherent MIMO communication, Grassmannian constellations, Gray labelling, combinatorial assignment problem, quadratic assignment problem.

“…When employed with iterative (soft) detection and decoding (IDD), BICM-encoded systems were shown in [18] to be capable of providing effective communication at rates close to the ergodic capacity of coherent MIMO communication systems. In [8] the BICM-IDD scheme was extended to non-coherent MIMO systems that use Grassmannian constellations. A generic BICM-IDD system adapted to non-coherent communication is shown in Figure 2.…”

Section: B a Bicm-idd Schemementioning

confidence: 99%

“…The work of the fifth author is supported in part by the Canada Research Chair program. capacity is to envelop a Grassmannian constellation in a bitinterleaved coded-modulation (BICM) framework [7], [8]. In this scheme the transmitter maps the output of the BICM encoder to channel symbols that are drawn from a capacityapproaching Grassmannian constellation.…”

Section: Introductionmentioning

confidence: 99%

Quasi-Gray labelling for Grassmannian constellations

2009 11th Canadian Workshop on Information Theory

Colman

El-Azizy

et al. 2009

Self Cite

This paper presents a technique for assigning binary labels to the points in an arbitrary Grassmannian constellation in a manner that approximates the Gray labelling. The idea behind this technique is to match the Grassmannian constellation of interest to the points in an auxiliary constellation that can be readily Gray labelled. In order to demonstrate the efficacy of the proposed technique, the labelled constellations are utilized in a BICM-encoded non-coherent MIMO communication system with iterative detection and decoding. Numerical simulations indicate that this labelling technique results in a non-coherent communication system that provides better bit error rate performance than systems that utilize the same constellation but employ labels that are generated either randomly or via a quasi-set-partitioning technique.