In closed loop methods for obtaining exact channel state information at the transmitter (CSI-Tx), the overhead associated with the feedback can be excessive for fast mobiles. Channel-statistics-based CSI-Tx requires a much smaller overhead, and is, therefore, attractive for use with fast mobiles. We study ways to exploit correlation-based CSI-Tx in a multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. We focus on a channel environment in which spatial and tap correlation are present. We propose a channel model for the case such that spatial and tap correlation can be separated, and show that this case channel correlation decreases the ergodic capacity of a MIMO-OFDM system when no CSI-Tx is available. However, this decrease can be mitigated when correlation based CSI-Tx is exploited. We introduce an optimal precoding approach to maximize capacity with spatial- and tap-correlation-based CSI-Tx. We also propose a statistical waterfilling scheme, which leads to almost optimal capacity performance without requiring computationally intensive numerical optimization. Based on these approaches, the impact of spatial and tap correlation is investigated.

In closed-loop methods for obtaining exact channel state information at the transmitter (CSI-Tx), the overhead associated with the feedback can be excessive for fast mobiles. Channel statistics-based CSI-Tx requires a much smaller overhead and is, therefore, attractive for use with fast mobiles. We study ways to exploit correlation-based CSI-Tx in a multiple-input multiple-output (MIMO)-orthogonal frequency-division multiplexing (OFDM) system. We focus on a channel environment in which spatial and tap correlations are present. We propose a channel model for the case that spatial and tap correlations can be separated and show that in this case channel correlation decreases the ergodic capacity of an MIMO-OFDM system when no CSI-Tx is available. However, this decrease can be mitigated when correlation-based CSI-Tx is exploited. We introduce an optimal precoding approach to maximize capacity with spatial and tap correlation-based CSI-Tx. We also propose a statistical waterfilling scheme, which leads to almost optimal capacity performance without requiring computationally intensive numerical optimization. Based on these approaches, the impact of spatial and tap correlations is investigated.

It is generally accepted that correlation reduces the capacity of the MIMO radio channel. Recently, however, it has been pointed out that several sources of correlation exist. Whereas most often in communications, correlation is interpreted in terms of spatial correlations due to the propagation environment, also the coupling between transmit and receive antennas has an impact on the capacity of a given communication channel. Against intuition, it has been claimed that in certain cases antenna coupling has a beneficial effect. In this paper, we derive a general expression for the correlation matrix of the MIMO channel and its dependence on both antenna coupling and spatial correlation. We show how the capacity of the MIMO channel depends on the eigenvalues of the antenna coupling matrices and study the interplay between spatial correlation and antenna coupling in the high SNR regime.

We propose to apply a technique called time-reversal to UWB communications. In time-reversal a signal is precoded such that it focuses both in time and in space at a particular receiver. Spatial focusing reduces interference to other co-existing systems. Due to temporal focusing, the received power is concentrated within a few taps and the task of equalizer design becomes much simpler than without focusing. Furthermore, temporal focusing allows a large increase in transmission rate compared to schemes that let the impulse response ring out before the next symbol is sent. Our paper introduces time-reversal, investigates the benefit of temporal focusing, and examines the performance of an MMSE-TR equalizer in an UWB channel.

We investigate the capacity behavior of an OFDM wireless link for the frequency selective MIMO channel with correlated paths. The derivation is based on a particular channel model that characterizes path correlation as well as spatial correlation. As in the case of spatial correlation, path correlation can reduce capacity. If there is no channel knowledge at the transmitter, the capacity reduction of an OFDM based system due to path correlation can be explained in terms of the effective SNR at each tone. With spatial and path correlation information at the transmitter, we derive the optimal space-frequency precoder at every tone by numerical optimization techniques. We propose a sub-optimal precoding scheme with lower complexity which leads to a tight lower bound of the capacity of the OFDM system.

This paper presents the geometrical technique investigation of the rank-1 Ricean MIMO channels at high SNR mutual information (MI) for Gaussian code books with no channel state information (CSI) at the transmitter and perfect CSI at the receiver. The analytical approximation for the probability density function (pdf), mean and variance of the MI that reveals the Gaussian nature of MI both in the Rayleigh and the rank-1 Ricean cases are also derived.

Radio interference from adjacent systems or users is an important limiting quantity for the transmission rate in wireless communications. Interference studies, however, often have the drawback that they are obtained from measurements in a particular environment. A more generally valid characterization for the interference power is highly desirable. In this paper, such an expression is analytically derived for a single link. The derivation is based on a simple, well-accepted pathloss law; furthermore, on a geometrically motivated transformation of the properties of the environment into expressions that depend only on the volume and surface of the domain in which transmitter and receiver are randomly located. This strategy yields a highly flexible and accurate approximation of the mean interference power as an analytical function of the key characteristics of wave propagation and the surroundings. The paper sheds also some light on the question why the stochastic radio channel is geometrically very robust. To the best knowledge of the author, this contribution is the first rigorous, non-empirical derivation of radio interference.

The paper introduces a model for the stochastic millimeter-wave indoor radio channel. This model relates the stochastic properties of the radio channel to the underlying geometry of the investigated environment. The geometric simplicity of the millimeter-wave channel allows examining fundamental deterministic properties of the wave propagation behavior in environments of predefined randomness, i.e., environments whose dimensions and properties are described by various probability distributions. The influence of the randomness on the radio channel is studied for the down-link of a wireless local area network at 60 GHz. Joint amplitudes of path lengths, angles of departure, and amplitudes, as well as spatial power densities, average power of the direct paths, and k factors are investigated.

The design of high frequency wireless local area networks requires knowledge about the radio channel within very small cells down to the size of single rooms. In this paper the power delay profile of a single room with homogeneous walls is calculated analytically. It is shown to be an exponential function that depends on the delay spread only, which itself is a function of the wall attenuation and the side length of the room. The derived expression can be easily implemented on any computer or programmable pocket calculator and describes very well the power delay profiles obtained by ray tracing simulations and measurements in many different scenarios such as closed and open rooms, non cubic rooms, and corridors.