Research On Signal Detection In LTE System

Since the emergence of wireless communications, the signal detection technology has also beendeveloped all the time. However, certain proportion of the traditional signal detectiontechnologies is not suitable for LTE system because of their high bit error rate or high computingcomplexity. Therefore, researching on the signal detection for the next generation of wirelesscommunications is necessary. This thesis firstly investigates the classical signal detection methods,including zero-forcing algorithm, minimum mean square error algorithm, interferencecancellation algorithm, QR detection algorithm, sphere decoding algorithm and so on.Based on the combination of QR detection algorithm, interference cancellation algorithm andsphere decoding algorithm, this thesis designs an adaptive grouping detection algorithm. Theadaptive grouping detection algorithm first modifies the Household QR decomposition, make thediagonal elements of R matrix decomposed from channel matrix H sort descending; then dividesthe symbol vector into sensitive symbol subgroup and reliable symbol subgroup by comparingthe SNR with the threshold which computed according to the expected complexity. The sensitivesymbol subgroup is preferentially detected by near-ML sphere decoding algorithm, while thereliable symbol subgroup is detected by sorted QR decomposition detection algorithm. Theadvantage of the algorithm is that it is easy to grouping the sensitive symbol and reliable symbol,avoids the real-time computing for system, and meets the needs of low latency of LTE system.Much more importantly, the algorithm combines the advantages of sorted QR decompositionalgorithm and sphere decoding algorithm, achieves the expected tradeoff between performanceand complexity. The simulation results prove the validity of the adaptive grouping detectionalgorithm.