Brian L. Hughes

Learn More
Space–time coding and modulation exploit the presence of multiple transmit antennas to improve performance on multipath radio channels. Thus far, most work on space–time coding has assumed that perfect channel estimates are available at the receiver. In certain situations, however, it may be difficult or costly to estimate the channel accurately, in which(More)
PURPOSE The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing(More)
Most existing space-time coding schemes assume time-invariant fading channels and offer antenna diversity gains relying on accurate channel estimates at the receiver. Based on a diagonal unitary matrix group, a novel double differential space-time block coding approach is derived in this paper for time-selective fading channels. Without estimating the(More)
The arbitrarily varying channel (AVC) can be interpreted as a model of a channel jammed by an intelligent and unpredictable adversary. We investigate the asymptotic reliability of optimal random block codes on Gaussian arbitrarily varying channels (GAVC’s). A GAVC is a discrete-time memoryless Gaussian channel with input power constraint PT and noise power(More)
The capacity of the discrete memoryless arbitrarily varying channel (AVC) is investigated for deterministic list codes with fixed list size L. For every AVC with positive random code capacity Cr, a nonnegative integer M called the symmetrizability is defined. For the average probability of error criterion, it is shown that the list capacity is given by C(L)(More)
We consider the asymptotic behavior of the capacity of multiple-antenna Rayleigh-fading channels in the limit as the transmit and receive arrays become large. We show that the capacity converges in distribution to a Gaussian random variable, and give closed-form formulas for its mean and variance. These results enable us to derive the first asymptotic(More)