Reduced-rank technique for joint channel estimation in TD-SCDMA systems.

In time division-synchronous code division multiple access systems, the channel estimation for multiple subscribers requires the computation of very complicated algorithms through short training sequences. This situation causes mismodeling of the actual channels and introduces significant errors in the detected data of multiple users. This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. Simulation results of the normalized mean square error for the above mentioned estimators showed the superiority of reduced rank estimators. Multi-user joint data detectors based linear equalizers are used to suppress inter-symbol interference and mitigate intra-cell multiple access interference. The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. The results of bit error rate simulation have shown that reduced rank-JCE based detectors have an improvement by 5 dB lower than other traditional full rank-JCE based detectors

Analysis of joint channel estimation and joint data detection in TD-SCDMA systems

Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) has several attractive characteristics that made it capable of meeting the requirements of G4 systems when applied as a platform directly. Joint detections, the unpaired spectrums with flexible sharing of resources, and some other advanced properties leads TD-SCDMA to achieve high data rate services. In this paper a comprehensive analysis is presented that involve accurate Joint Channel Estimation (JCE) for traditional and enhanced estimators based on two criterions: Least square (LS) & Minimum Mean Square Error (MMSE) at two scenarios of users' movements. In addition to a comprehensive Multi-Users Joint Detection (MUJD) is improved to mitigate Multiple Access Interference (MAI) and Inter-Symbol Interference (ISI) using the following detectors: Matched Filter (MF), Zero Forcing Block Linear Equalizer (ZF-BLE), and Minimum Mean Square Error Block Linear Equalizer (MMSE-BLE) for traditional and enhanced channel estimation criterions. Simulation results showed that equalizers fed by Channel Impulse Response (CIR) optimized according to enhanced LS or MMSE give a better performance to that ones when CIR obtained from traditional LS or MMSE criterion. The using of MMSE give the opportunity to implement adaptive equalizes to cope with fast fading and/or non stationary interference environments