遥感影像解译算法的研究进展

系统地分析了遥感影像解译算法的研究现状及存在的问题 。

A Memory Efficient Belief Propagation Decoder for Polar Codes

Polar codes have become increasingly popular recently because of their capacity achieving property.In this paper,a memory efficient stage-combined belief propagation(BP) decoder design for polar codes is presented.Firstly,we briefly reviewed the conventional BP decoding algorithm.Then a stage-combined BP decoding algorithm which combines two adjacent stages into one stage and the corresponding belief message updating rules are introduced.Based on this stage-combined decoding algorithm,a memory-efficient polar BP decoder is designed.The demonstrated decoder design achieves 50%memory and decoding latency reduction in the cost of some combinational logic complexity overhead.The proposed decoder is synthesized under TSMC 45 nm Low Power CMOS technology.It achieves 0.96 Gb/s throughput with 14.2mm^2 area when code length N=2^(16)which reduces 51.5%decoder area compared with the conventional decoder design.

REDUCED-COMPLEXITY DECODING ALGORITHMS FOR UNITARY SPACE-TIME CODES

Two reduced-complexity decoding algorithms for unitary space-time codes based on tree-structured constellation are presented. In this letter original unitary space-time constellation is divided into several groups. Each one is treated as the leaf nodes set of a subtree. Choosing the unitary signals that represent each group as the roots of these subtrees generates a tree-structured constellation. The proposed tree search decoder decides to which sub tree the receive signal belongs by searching in the set of subtree roots. The final decision is made after a local search in the leaf nodes set of the se-lected sub tree. The adjacent subtree joint decoder performs joint search in the selected sub tree and its “surrounding” subtrees,which improves the Bit Error Rate (BER) performance of purely tree search method. The exhaustively search in the whole constellation is avoided in our proposed decoding al-gorithms,a lower complexity is obtained compared to that of Maximum Likelihood (ML) decoding. Simulation results have also been provided to demonstrate the feasibility of these new methods.

Design and Implementation of a Novel Algorithm for Iterative Decoding of Product Codes

A novel product code iterative decoding algorithm and its high speed implementation scheme are proposed in this paper. Based on partial combination of selected columns of check matrix, the reduced-complexity syndrome decoding method is proposed to decode sub-codes of product code and deliver soft output information. So iterative decoding of product codes is possible. The fast sorting algorithm and a look-up method are proposed for high speed implementation of this algorithm. Compared to the conventional weighing iterative algorithm, the proposed algorithm has lower complexity while offering better performance, which is demonstrated by simulations and implementation analysis. The implementation scheme and verilog HDL simulation show that it is feasible to achieve high speed decoding with the proposed algorithm.

A new probability decoding scheme based on genetic algorithm for FEC codes in optical transmission systems

Based on the genetic algorithm(GA),a new genetic probability decoding(GPD) scheme for forward error correction(FEC) codes in optical transmission systems is proposed.The GPD scheme can further offset the quantification error of the hard decision by making use of the channel interference probability and statistics information to restore the maximal likelihood transmission code word.The theoretical performance analysis and the simulation result show that the proposed GPD scheme has the advantages of lower decoding complexity,faster decoding speed and better decoding correction-error performance.Therefore,the proposed GPD algorithm is a better practical decoding algorithm.