We propose a space–time block coding framework based on linear precoding. The codes for$P$transmit antennas are formed by transmitting the information vector (with$P$independent information symbols)$L$times where each time it is rotated by a distinct precoding matrix. The framework generalizes conventional spatial multiplexing techniques and facilitates tradeoff between rate and diversity. We propose a simple construction for precoding matrices whose parameters are chosen to guarantee maximal diversity using algebraic number theory. Our codes exhibit circular structure, which greatly simplifies the performance analysis and facilitates linear decoding. Theoretical analysis and numerical simulations demonstrated excellent performance of the proposed algebraic precoding framework.

We consider a wireless network composed of three nodes and limited by the half-duplex and total power constraints. This formulation encompasses many of the special cases studied in the literature and allows for capturing the common features shared by them. Here, we focus on three special cases, namely, 1) relay channel, 2) multicast channel, and 3) three-way channel. These special cases are judicially chosen to reflect varying degrees of complexity while highlighting the common ground shared by the different variants of the three-node wireless network. For the relay channel, we propose a new cooperation scheme that exploits the wireless feedback gain. This scheme combines the benefits of the decode-and-forward (DF) and compress-and-forward (CF) strategies and avoids the noiseless feedback assumption adopted in earlier works. Our analysis of the achievable rate of this scheme reveals the diminishing feedback gain in both the low and high signal-to-noise ratio (SNR) regimes. Inspired by the proposed feedback strategy, we identify a greedy cooperation framework applicable to both the multicast and three-way channels. Our performance analysis reveals the asymptotic optimality of the proposed greedy approach and the central role of list source-channel decoding in exploiting the receiver side information in the wireless network setting.

We propose an iterative extension of the Bell Laboratory Layered Space-Time (BLAST) algorithm and its variant, vertical BLAST (VBLAST). A characteristic feature of the BLAST-type algorithm is that symbol decisions with low reliability are fed back to decode other symbols. Both performance analysis based on Gaussian approximation of residual interference, and simulation results demonstrate that error propagation due to unreliable decision feedback can severely limit system performance. The extended algorithm exploits inherent signal diversity in BLAST to mitigate residual interference, thus overcoming the performance bottleneck due to error propagation. It yields an impressive performance gain over BLAST. In particular, the extension of BLAST with zero-forcing interference nulling admits a simple QR implementation and exhibits excellent performance with low complexity.

We propose a novel decentralized detection scheme based on the method of types and type detectors. Contrary to conventional methods, the proposed decentralized type detection (DTD) scheme asymptotically achieves the performance of centralized detection, provided there exists an arbitrarily small (but non-zero) communication capacity between the sensing nodes and the decision center. The sensing nodes extract and transmit the type information of the observed data sequence, which is then recovered and used by a type detector at the decision center. The key to DTD is that the required network information flow (type information) is of asymptotically vanishing entropy rate but still sufficient for the hypothesis testing problem. The simple structure of type sensors greatly reduces system cost in terms of computational and communication capabilities for sensor nodes. In particular, the sensor nodes need not know the signal statistics under different hypothesis. Theoretical analysis and numerical simulations demonstrate the excellent performance of the proposed DTD scheme.

This paper develops a general framework for communication over doubly dispersive fading channels via an orthogonal short-time Fourier (STF) basis. The STF basis is generated from a prototype pulse via time-frequency shifts. In general, the orthogonality between basis functions is destroyed at the receiver due to channel dispersion. The starting point of this work is a pulse scale adaptation rule first proposed by Kozek to minimize the interference between the basis functions. We show that the average signal-to-interference-and-noise (SINR) ratio associated with different basis functions is identical and is maximized by the scale adaptation rule. The results in this paper highlight the critical impact of the channel spread factor, the product of multipath and Doppler spreads, on system performance. Smaller spread factors result in lesser interference such that a scale-adapted STF basis serves as an approximate eigenbasis for the channel. A highly effective iterative interference cancellation technique is proposed for mitigating the residual interference for larger spread factors. The approximate eigendecomposition leads to an intuitively appealing block-fading interpretation of the channel in terms of time-frequency coherence subspaces: the channel is highly correlated within each coherence subspace whereas it is approximately independent across different subspaces. The block-fading model also yields an approximate expression for the coherent channel capacity in terms of parallel flat-fading channels. The deviation of the capacity of doubly dispersive channels from that of flat-fading channels is quantified by studying the moments of the channel eigenvalue distribution. In particular, the difference between the moments of doubly dispersive and flat-fading channels is proportional to channel spread factor. The results in this paper indicate that the proposed STF signaling framework is applicable for spread factors as large as 0.01.

We apply the recently introduced virtual channel representation to the problem of space-time coding for correlated multiple-input multiple-output (MIMO) channels. The virtual channel representation clearly reveals the essential degrees of freedom in correlated MIMO channels and the corresponding statistical channel structure. Coding design criteria for general correlated channels are derived from pairwise error probability analysis, which reveal the effect of channel statistics and codeword properties on code performance. We focus on the K-diagonal model for correlated channels whose nonvanishing elements correspond to K diagonals of the virtual channel matrix. The K-diagonal model can be motivated by physical scattering considerations or as a low-dimensional approximation to the channel matrix that serves as a building block for general correlated channels. Space-time D-block codes that attain D-level diversity (related to K) per receive dimension are constructed using the theory of space-time block codes. Compared with space-time block codes, identical performance but with significantly smaller delay and complexity can be achieved by matching space-time D-block codes to the K-diagonal channel structure. Our construction also facilitates a natural tradeoff between rate and diversity by decomposing the original channel into several parallel virtual K-diagonal subchannels. Simulation results demonstrate the excellent performance of the proposed techniques.

Multi input multi output (MIMO) channels under a particular set of correlated channel assumptions, viz. the product correlation, have been shown to differ from i.i.d. channels essentially in the scaling factor of capacity increase [Chen-Nee Chuah, et al. (2002)]. Using a scattering environment based channel representation, we extend the paradigm of capacity scaling to a regime where it saturates or scales depending on how the environment grows with the number of antennas. We also show how the capacity per dB at low SNR's depends on the channel parameters. Based on some (preliminary) results on the convergence rate of the empirical spectral distribution function of an i.i.d. channel we present a rigorous understanding of the notion of 'fast convergence'.

Spatial multiplexing techniques send independent data streams on different transmit antennas to maximally exploit the capacity of multiple-input multiple-output (MIMO) fading channels. Most existing multiplexing techniques are based on an idealized MIMO channel model representing a rich scattering environment. Realistic channels corresponding to scattering clusters exhibit correlated fading and can significantly compromise the performance of such techniques. In this paper, we study the design and performance of spatial multiplexing techniques based on a virtual representation of realistic MIMO fading channels. Since the nonvanishing elements of the virtual channel matrix are uncorrelated, they capture the essential degrees of freedom in the channel and provide a simple characterization of channel statistics. In particular, the pairwise-error probability (PEP) analysis for correlated channels is greatly simplified in the virtual representation. Using the PEP analysis, various precoding schemes are introduced to improve performance in virtual channels. Unitary precoding is proposed to provide robustness to unknown channel statistics. Nonunitary precoding techniques are proposed to exploit channel structure when channel statistics are known at the transmitter. Numerical results are presented to illustrate the attractive performance of the precoding techniques.

The dramatic linear increase in ergodic capacity with the number of antennas promised by multiple-input multiple-output (MIMO) wireless communication systems is based on idealized channel models representing a rich scattering environment. Is such scaling sustainable in realistic scattering scenarios? Existing physical models, although realistic, are intractable for addressing this problem analytically due to their complicated nonlinear dependence on propagation path parameters, such as the angles of arrival and delays. In this paper, we leverage a recently introduced virtual representation of physical models that is essentially a Fourier series representation of wide-band MIMO channels in terms of fixed virtual angles and delays. Motivated by physical considerations, we propose a D-connected model for correlated channels defined by a virtual spatial channel matrix consisting of D nonvanishing diagonals with independent and identically distributed (i.i.d.) Gaussian entries. The parameter D provides a meaningful and tractable measure of the richness of scattering. We derive general bounds for the coherent ergodic capacity and investigate capacity scaling with the number of antennas and bandwidth. In the large antenna regime, we show that linear capacity scaling is possible if D scales linearly with the number of antennas. This, in turn, is possible if the number of resolvable paths grows quadratically with the number of antennas. The capacity saturates for linear growth in the number of paths (fixed D). The ergodic capacity does not depend on frequency selectivity of the channel in the wide-band case. Increasing bandwidth tightens the bounds and hastens the convergence of scaling behavior. For large bandwidth, the capacity scales linearly with the signal-to-noise ratio (SNR) as well. We also provide an explicit characterization of the wide-band slope recently proposed by Verdu. Numerical results are presented to illustrate the key theoretical results.

We analyze space-time block codes for transmit diversity utilization from a signal processing viewpoint. The study shows that space-time block codes are not able to efficiently exploit all available signal space dimensions. In particular, the rate limitation of space-time block codes incurs a large capacity penalty. We propose a novel signal processing technique, layered transmit diversity, which achieves full rate transmission. The technique combines interference cancellation processing in the Bell Laboratory Layered Space-Time (BLAST) architecture and space-time block coding to jointly process real and imaginary parts of received signals. it is shown that layered transmit diversity can approach channel capacity.

We introduce a new signaling scheme for time- and frequency-selective channels that is a generalization of multi-carrier code division multiple access (MC-CDMA) signaling used in slowly time-varying channels. The Fourier basis functions used in conventional MC-CDMA systems encounter temporal distortion in rapidly time-varying channels resulting in degraded performance. The proposed scheme transmits the data over a set of orthonormal time-frequency basis functions whose time-frequency support is matched to the coherence time and bandwidth of the channel. The time-frequency signaling scheme approximately diagonalizes the time-varying multipath channel and each basis function encounters flat Rayleigh fading. We derive an optimal choice of basis parameters that yield the most accurate diagonalization for given multipath and Doppler spreads of the channel. The proposed system fully exploits the diversity afforded by the channel and delivers improved performance in rapidly time-varying channels in contrast to degraded performance of existing systems under such conditions.