Multi-User Detection Based on Improved-KICA
In this paper Improved kernel independent component analysis (KICA) algorithm is proposed for detection of direct sequence code division multiple access ( DS-CDMA ) signals and compared with KICA and FastlCA algorithms. ICA based technique is based on independence of source signals and these conditions are satisfied in multi-user CDMA environment. The aim is to recover a set of unknown mutually independent source signals from their observed mixtures without knowledge of the mixing coefficients. KICA which is advanced recently is a non-linear method for blind source separation (BSS).Combining a KICA element to conventional signal detection reduces multiple access interference (MAI) and enables a robust, computationally efficient structure. For traditional KICA algorithm is influenced by kernel function and also ignores noise, in this paper Improved-KICA algorithm using optimal kernel function and considering the noise is proposed for multi-user DSCDMA signal. In this paper bit error rate simulations of these algorithms has been given for different number of users, SNR and compared. The results show that the proposed Improved-KICA is more effective compared with traditional algorithms and performs better at separating the source signals from the mixed CDMA signals with noise.
multi-user detection DS-CDMA Improved-KICA KPCA KICA FastlCA
Liu Xiaozhi Han Ying Li Xiang Yang Yinghua
College of Information Science and Engineering Northeastern University Shenyang, China
国际会议
2011 International Conference on Electronics and Optoelectronics(2011电子学与光电子学国际会议 ICEOE 2011)
大连
英文
173-176
2011-07-29（万方平台首次上网日期，不代表论文的发表时间）