Gregory G. Raleigh

Spatio-temporal coding for wireless communication

Multipath signal propagation has long been viewed as an impairment to reliable communication in wireless channels. This paper shows that the presence of multipath greatly improves achievable data rate if the appropriate communication structure is employed. A compact model is developed for the multiple-input multiple-output (MIMO) dispersive spatially selective wireless communication channel. The multivariate information capacity is analyzed. For high signal-to-noise ratio (SNR) conditions, the MIMO channel can exhibit a capacity slope in bits per decibel of power increase that is proportional to the minimum of the number multipath components, the number of input antennas, or the number of output antennas. This desirable result is contrasted with the lower capacity slope of the well-studied case with multiple antennas at only one side of the radio link. A spatio-temporal vector-coding (STVC) communication structure is suggested as a means for achieving MIMO channel capacity. The complexity of STVC motivates a more practical reduced-complexity discrete matrix multitone (DMMT) space-frequency coding approach. Both of these structures are shown to be asymptotically optimum. An adaptive-lattice trellis-coding technique is suggested as a method for coding across the space and frequency dimensions that exist in the DMMT channel. Experimental examples that support the theoretical results are presented.

Spatio-temporal coding for wireless communications

A compact model is derived for the multiple-input multiple output (MIMO), dispersive, spatially selective wireless communication channel. The multivariate information capacity behavior is then analyzed for various input and output antenna configurations. For high SNR conditions, the MIMO channel can exhibit a capacity slope in bits per dB of power increase that is proportional to the minimum of the number multipath components, the number of input antennas, or the number of output antennas. The discrete matrix multitone (DMMT) is proposed as an asymptotically optimal, practical spatio-temporal coding structure. Experimental examples that support the theoretical results are presented.

A blind adaptive transmit antenna algorithm for wireless communication

A method is proposed for forming an adaptive phased array transmission beam pattern at a base station without any knowledge of array geometry, path angles or mobile feedback. Estimates of receive vector channels are used to form a transmit weight vector optimization problem. The authors provide closed form solutions for both the single user case and the multiple user case. They show through simulation of a multiple user cellular network that the cooperative transmission network algorithm is capable of improving network frequency re-use capacity by a factor of 5 to 8.

Characterization of fast fading vector channels for multi-antenna communication systems

In a wireless communication environment, multipath propagation and mobile user motion result in a dispersive time-varying communication channel. In order to analyze the performance of wireless communication systems, it is necessary to define models which reasonably approximate the time varying impulse response of the radio channel. Many widely accepted scalar channel (single antenna) statistical models have been reported. In order to analyze performance for real time adaptive antenna array techniques, it is necessary to extend existing scalar channel statistical models to the vector channel (multiple antenna) case. The paper develops a statistical, time varying, dispersive, wireless vector channel model which is based on the physical propagation environment. The model is shown to be consistent with the known characteristics of the wireless communication channel. Antenna pattern interference rejection as a function of update rate is presented as an application example for the vector channel model.<<ETX>>

Time varying vector channel estimation for adaptive spatial equalization

New blind adaptive spatial equalization techniques are proposed for severe multipath fading with co-channel interference. In rapidly fading environments, equalizer performance suffers with existing algorithms because the desired and interference channels change significantly over the update time interval. It is shown that for fast fading channels, conventional squared error equalizer cost functions can yield poor results. A new algorithm is proposed based on a variation of the SINR cost function coupled with optimal time varying channel estimation to improve signal tracking. In simulations, the algorithm achieves theoretically optimum time varying equalizer performance in extreme interference channels with narrow band FM signals and high velocity portables. These results are contrary to the widespread belief that high performance blind adaptive array processing is not possible for AMPS with severe combinations of Doppler spread, angle spread, and interference power.

Estimation of co-channel FM signals with multitarget adaptive phase-locked loops and antenna arrays

A simple adaptive technique is proposed for separation and demodulation of multiple co-channel frequency modulated (FM) signals received at an antenna array. The proposed method, which for FM signals is embodied in an architecture referred to as a multitarget adaptive phase-lock loop (MADPLL), exploits known signal structure through a complete demodulation and remodulation of the signals. The two properties of the signal that are exploited here are the known bandwidth of the information signal and the constant-modulus (CM) property of FM signals. It is shown that the proposed method can lead to significant improvements in performance over methods that exploit only the CM property.