Tota Suko

An Algorithm for Computing the Secrecy Capacity of Broadcast Channels with Confidential Messages

In this paper, we present an iterative algorithm for computing the secrecy capacity of broadcast channel with confidential message (BCC) in the situation that the main channel is less noisy than the eavesdroppers channel. The global convergence of the algorithm is proved, and an expression for its convergence rate is derived.

Multiuser Detection Algorithm for CDMA Based on the Belief Propagation Algorithm

Optimum detection for the multiuser code-division multiple-access channel is prohibitively complex. This paper considers new iterative multiuser detection algorithm based on the belief propagation algorithm. Previously, the idea to apply the belief propagation algorithm to multiuser detection problem was suggested , however, it was believed that to apply the belief propagation algorithm to the detection problem is impossible because it requires an exponentially large amount of computation. It was the only fact that the parallel interference canceller is derived as an approximation of the belief propagation. In this paper, we show that the belief propagation algorithm can be applied to the detection problem by converting the factor graph structure. Performance of the detector based on the belief propagation algorithm is better than that of the parallel interference canceller.

Iterative multiuser joint decoding based on ADMM

In this paper, we develop an iterative multiuser joint decoding of code-division multiple-access (CDMA) signals based on a distributed optimization algorithm. For the joint decoding problem, decoding algorithm based on the turbo principle is widely used. The algorithm consists of soft-input soft-output (SISO) channel decoder and SISO multiuser detector and it can be derived as an application of the sum-product algorithm. On the other hand, in the research area of error correcting codes, the decoding algorithm based on convex optimization has been attracting a great deal of attention. Decoding algorithm based on linear programming (LP) has decoding error rate which is comparable with sum-product algorithm with stronger theoretical guarantees. We formulate the joint decoding problem of CDMA signals as an convex optimization problem and we present a relax form of the problem. Moreover, we propose a distributed algorithm which efficiently solves the relaxed optimization problem. The proposed algorithm is based on alternating direction method of multipliers (ADMM). We also see the performance of the proposed decoder through numerical simulations.

Asymptotic property of universal lossless coding for independent piecewise identically distributed sources

Abstract The universal lossless source coding problem is one of the most important problem in communication systems. The aim of source coding is to compress data to reduce costs in digital communication. Traditional universal source coding schemes are usually designed for stationary sources. Recently, some universal codes for nonstationary sources have been proposed. Independent piecewise identically distributed (i.p.i.d.) sources are simple nonstationary sources that parameter changes discontinuously. In this paper, we assume new i.p.i.d. sources class, and we prove that Bayes codes minimize the mean redundancy when parameter transition pattern is known and parameter is unknown.