Code Rate

The most common concern of any communication system is the data quality. There exist different components that can impact the quality of data during its conveying over the channel as noise, fading, etc. Forward error correcting codes (FEC) play a major role for overcoming this noise as it adds a control bits to the original data for error detection and correction. This paper aims at analyzing convolutional codes with different rates and evaluating its performance. Binary phase shift modulation (BPSK) scheme and binary symmetric channel (BSC) model are used. First a convolution encoder is presented and then additive white Gaussian noise (AWGN) is added. The paper uses maximum likelihood mechanism (Vetribi Algorithm) for decoding process. Simulations are carried out using MATLAB with Simulink tools. Bit error rate (BET) is used as testing parameter and results of system behavior for both coded and encoded are compared.

Abstract—In this paper, a powerful class of irregular low-density parity check (LDPC) codes based on random construction techniques is presented. The resultant codes have accurate profile with the additional features of making them suitable for incremental redundancy systems. The ...

Maximum likelihood soft-decision decoding of linear block codes is addressed in this correspondence. A novel algorithm based on Chase-2 algorithm for the decoding of systematic binary block codes is detailed. A double re-encoding technique in place of the classical algebraic decoding for the computation of the candidate codeword list is the major innovation of the proposed algorithm. This approach has

... Goran M. Djuknic and Donald L. Schilling ... The combined random process, consisting of all trail arrivals, is also Poisson, with the parameter h = h, + h,. Consequently, themeantimebetween trail arrivals in this new process is t , = Ilk. ...

We construct a new family of linear space-time (ST) block codes by the combination of rotated constellations and the Hadamard transform, and we prove them to achieve the full transmit diversity over a quasi-static or fast fading channels. The proposed codes transmit at a normalized rate of 1 symbol/s. When the number of transmit antennas n=1, 2, or n is a multiple of four, we spread a rotated version of the information symbol vector by the Hadamard transform and send it over n transmit antennas and n time periods; for other values of n, we construct the codes by sending the components of a rotated version of the information symbol vector over the diagonal of an n × n ST code matrix. The codes maintain their rate, diversity, and coding gains for all real and complex constellations carved from the complex integers ring Z [i], and they outperform the codes from orthogonal design when using complex constellations for n > 2. The maximum-likelihood (ML) decoding of the proposed codes can be implemented by the sphere decoder at a moderate complexity. It is shown that using the proposed codes in a multiantenna system yields good performances with high spectral efficiency and moderate decoding complexity