Higher Mutual Information Research Articles

Bandwidth-efficient wireless OFDM

Due to ever-increasing bandwidth demands in future wireless service, the radio frequency band becomes more and more invaluable. In this paper, we address channel equalization for bandwidth-efficient wireless orthogonal frequency-division multiplexing (OFDM). First, we show that in order to be free of both interchannel interference and interblock interference, wireless OFDM has to occupy a bandwidth wider than the Nyquist rate and use insufficient statistics in symbol demodulation. Thus, the conventional OFDM gains computational efficiency using the discrete Fourier transform (DFT) in demodulation at the cost of low efficiency of bandwidth usage and degradation in symbol error performance. Then we consider the OFDM that achieves high efficiency of bandwidth usage, allows interchannel interference and interblock interference to exist, and uses sufficient statistics in symbol demodulation. A one-tap decision feedback equalizer (DFE) is proposed for equalization of the bandwidth efficient OFDM system. Simulation and numerical evaluation for an indoor wireless asynchronous transfer mode network are carried out. It is demonstrated that though occupying a narrower bandwidth, the one-tap DFE-based bandwidth-efficient OFDM system achieves lower symbol error rate and higher mutual information than the conventional DFT-based OFDM system. The proposed OFDM system presents a monotonically increasing symbol error rate, and convex-down achieved mutual information with respect to increasing efficiency of bandwidth usage.

Radial Basis Function Network Configuration Using Mutual Information and the Orthogonal Least Squares Algorithm

Input nodes of neural networks are usually predetermined by using a priori knowledge or selected by trial and error. For example, in pattern recognition applications the input nodes are usually the given pattern features and in system identification applications the past input and output data are often used as inputs to the network. Some of the input variables may be irrelevant to the task in hand and therefore may cause a deterioration in network performance. Some may be redundant and may increase the complexity of the network and consume expensive computation time. In the present study, the mutual information between the input variables and the output of the network is used to select a suboptimal set of input variables for the network. The variables are selected according to the information content relevant to the output. Variables which have a higher mutual information with the output and lower dependence on other selected variables are used as network inputs. The algorithms are derived based on heuristics and performance is assessed by using radial basis function (RBF) networks trained with the orthogonal least squares algorithm (OLS), which selects the hidden layer nodes of the network according to the error reduction ratios on the network output. Both real and simulated data sets are used to demonstrate the effectiveness of the new algorithms. Copyright © 1996 Elsevier Science Ltd.

Covariation of mutations in the V3 loop of human immunodeficiency virus type 1 envelope protein: an information theoretic analysis.

The V3 loop of the human immunodeficiency virus type 1 (HIV-1) envelope protein is a highly variable region that is both functionally and immunologically important. Using available amino acid sequences from the V3 region, we have used an information theoretic quantity called mutual information, a measure of covariation, to quantify dependence between mutations in the loop. Certain pairs of sites, including non-contiguous sites along the sequence, do not have independent mutations but display considerable, statistically significant, covarying mutations as measured by mutual information. For the pairs of sites with the highest mutual information, specific amino acids were identified that were highly predictive of amino acids in the linked site. The observed interdependence between variable sites may have implications for structural or functional relationships; separate experimental evidence indicates functional linkage between some of the pairs of sites with high mutual information. Further specific mutational studies of the V3 loop's role in determining viral phenotype are suggested by our analyses. Also, the implications of our results may be important to consider for V3 peptide vaccine design. The methods used here are generally applicable to the study of variable proteins.