Cooperative diversity is a transmission technique, where multiple terminals pool their resources to form a virtual antenna array that realizes spatial diversity gain in a distributed fashion. In this paper, we examine the basic building block of cooperative diversity systems, a simple fading relay channel where the source, destination, and relay terminals are each equipped with single antenna transceivers. We consider three different time-division multiple-access-based cooperative protocols that vary the degree of broadcasting and receive collision. The relay terminal operates in either the amplify-and-forward (AF) or decode-and-forward (DF) modes. For each protocol, we study the ergodic and outage capacity behavior (assuming Gaussian code books) under the AF and DF modes of relaying. We analyze the spatial diversity performance of the various protocols and find that full spatial diversity (second-order in this case) is achieved by certain protocols provided that appropriate power control is employed. Our analysis unifies previous results reported in the literature and establishes the superiority (both from a capacity, as well as a diversity point-of-view) of a new protocol proposed in this paper. The second part of the paper is devoted to (distributed) space-time code design for fading relay channels operating in the AF mode. We show that the corresponding code design criteria consist of the traditional rank and determinant criteria for the case of colocated antennas, as well as appropriate power control rules. Consequently space-time codes designed for the case of colocated multiantenna channels can be used to realize cooperative diversity provided that appropriate power control is employed.

Abstract-We consider compressed sensing of block-sparse signals, i.e., sparse signals that have nonzero coefficients occurring in clusters. An uncertainty relation for block-sparse signals is derived, based on a block-coherence measure, which we introduce. We then show that a block-version of the orthogonal matching pursuit algorithm recovers block k-sparse signals in no more than k steps if the block-coherence is sufficiently small. The same condition on block-coherence is shown to guarantee successful recovery through a mixed 2/ 1-optimization approach. This complements previous recovery results for the block-sparse case which relied on small block-restricted isometry constants. The significance of the results presented in this paper lies in the fact that making explicit use of block-sparsity can provably yield better reconstruction properties than treating the signal as being sparse in the conventional sense, thereby ignoring the additional structure in the problem.

On the other hand, several MIMO configurations have been considered to compare performances in terms of channel capacity including electromagnetic parameters of the antenna, such as radiation patterns and mutual coupling. The Spatial Channel Model from 3 GPP has been used for the simulations. Higher capacity has been obtained in the configuration where the two antennas has been placed in parallel with a spacing of 0.4 wavelengths within a PDA, mainly due to the lower mutual coupling and thus to uncorrelation between MIMO subchannels. Moreover, the radiation pattern for both antennas has been measured and MIMO channel measurement have been carried our in an indoor environment, obtaining in average higher capacity in the case of the designed PIFAs. ACKNOWLEDGMENTThe authors wish to thank S.R.F. Moyano, from Dragados Industrial, especially to Mr. Alberto Martínez Ollero, for the support of this research work conducted as part of the PIDEA SMART project and partially funded by PROFIT FIT-330210 -2005-107

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Abstract-Multiple-input multiple-output (MIMO) detection algorithms providing soft information for a subsequent channel decoder pose significant implementation challenges due to their high computational complexity. In this paper, we show how sphere decoding can be used as an efficient tool to implement softoutput MIMO detection with flexible trade-offs between computational complexity and (error rate) performance. In particular, we provide VLSI implementation results which demonstrate that single tree-search, sorted QR-decomposition, channel matrix regularization, log-likelihood ratio clipping, and imposing runtime constraints are the key ingredients for realizing soft-output MIMO detectors with near max-log performance at a chip area that is only 58% higher than that of the best-known hard-output sphere decoder VLSI implementation.Index Terms-Multiple-input multiple-output (MIMO) communication systems, soft-output sphere decoding, VLSI implementation, MIMO detection.

Abstract-This paper deals with the capacity behavior of wireless orthogonal frequency-division multiplexing (OFDM)-based spatial multiplexing systems in broad-band fading environments for the case where the channel is unknown at the transmitter and perfectly known at the receiver. Introducing a physically motivated multiple-input multiple-output (MIMO) broad-band fading channel model, we study the influence of physical parameters such as the amount of delay spread, cluster angle spread, and total angle spread, and system parameters such as the number of antennas and antenna spacing on ergodic capacity and outage capacity. We find that, in the MIMO case, unlike the single-input single-output (SISO) case, delay spread channels may provide advantages over flat fading channels not only in terms of outage capacity but also in terms of ergodic capacity. Therefore, MIMO delay spread channels will in general provide both higher diversity gain and higher multiplexing gain than MIMO flat-fading channels.Index Terms-Broad-band fading channels, diversity gain, ergodic capacity, MIMO, multiplexing gain, OFDM, outage capacity.