Search

In outdoor environments, waves propagate nonisotropically because of non-uniform distribution of scatterers. In addition directional antennas, which are efficient for communication applications, have considerable impact on the response of the communication channel. The impact of nonisotropic propagation and directional antennas is more significant when the system employs multiple antennas. In this paper, we propose a space-time-frequency cross-correlation function (CCF) for multiple-input multiple-output multicarrier channels in a two-dimensional (2D) random scattering medium. The expression of the CCF turns out to be a multiplication of three CCFs. Two of these terms characterize the impact of mobile station and base station, respectively and are linear Bessel expansions, where the coefficients are given by the linear convolution of the Fourier series coefficients (FSC)s of the employed antenna patterns and the FSCs of the probability density function describing 2D nonisotropic environment. The third expression characterizes the impact of the wireless channel. In the stationary case, we derive the expression of the fading channel power spectrum (CPS) in terms of the non-isotropic pdf and antenna patterns. Using the expression of the CCF, we also calculate coherence-bandwidth (CB)/coherence-time (CT) as a function of carrier-frequency/time separations. Our numerical results show a good fit to the available experimental results obtained for the CB/CT of realistic outdoor channels. Index Terms--MIMO wireless channel, space-time-frequency cross-correlation function, random scattering media, nonisotropic propagation channel, directional antennas, coherencetime, coherence-bandwidth and power spectral density.

We propose computationally inexpensive and efficient solutions for signal activity detection of phase-shift keying (PSK) signals in additive white Gaussian noise. We consider the complex amplitude of the signal, as well as the information sequence, as the unknown parameters. In addition, the noise variance is assumed unknown. We derive the generalized likelihood ratio test (GLRT) and suggest a computationally efficient implementation thereof. Furthermore, we develop a new inexpensive detector for binary PSK signals, which we will refer to as the generalized energy detector. To evaluate the performance of these detectors, we attempt to derive a uniformly most powerful invariant (UMPI) test as an optimal detector. It turns out that the UMPI test exists only if the signal-to-noise ratio is known. We use this UMPI test in order to obtain an upper-bound performance for the evaluation of invariant detectors, such as the GLRT. Simulation results illustrate and compare the performance and the efficiency of the proposed signal activity detectors. Index Terms--Additive Gaussian noise, binary detection problem, detection algorithms, generalized energy detector, generalized likelihood ratio (GLR), GLR detectors, invariances, invariant detectors, invariant hypothesis testing, matched filter detectors, maximal invariant statistic, maximum-likelihood (ML) detection, phase-shift keying (PSK), signal activity detection, signal classification, signal detection, uniformly most powerful invariant (UMPI) test.

A synchronized per survivor processing (PSP) maximum likelihood sequence detection (MLSD) receiver is presented for a fast frequency-selective Rayleigh fading channel and large carrier frequency offset. It is shown that, by incorporating the syn-chronization parameters (the timing error, carrier frequency and phase offsets) into the channel-impulse response (CIR) and modifying the resulting state-space model by a differential approach, the time-varying carrier frequency offset can be effectively tracked using a simple least mean square (LMS) estimator. New criteria are proposed based on the smoothness of the estimated channel derivatives. New criteria are proposed based on this fact that, for smoothly time-varying CIR and frequency offset, the magnitude of the CIR time derivative compared with the magnitude of CIR should be very small. It is illustrated that the new criteria and the conventional mean square error (MSE) are complementary. Index Terms--Adaptive equalizers, adaptive Kalman filtering, data communication, maximum-likelihood detection, maximum-likelihood sequence estimation, phase synchronization, synchronization, time-divison multiple access, tracking.