Single tree search sphere decoding algorithm for MIMO communication system

Multiple Input Multiple Output (MIMO) systems utilize many antennas at both transmitter and receiver for higher Bandwidth efficiency. The implementation of MIMO detection becomes a difficult task as the computational complexity increases with the number of transmitting antenna and constellation size increases. The decoder for a 4*4 MIMO system with 16-QAM modulation and spatial multiplexing is implemented using Mat lab. Difficult part is MIMO detection; ML decoding cannot be implemented directly because increase the complexity exponentially if size of constellation and number of transmit antenna increases. Sphere decoding reduce the complexity of decoding with some improvement with the decoding rate and BER. In my project sphere decoding combined with single tree search and ML decoding greatly improve the decoding Rate and BER. In sphere decoding selecting the sphere radius is very important. Sphere decoding algorithm implemented in the tree search complexity of algorithm is more reduced. In tree search Tree pruning strategies are used to reduce the more difficulty in the tree search based algorithms. The basic idea is to reduce the number of tree nodes visited to achieve a ML result. The decision where to visit a node or prune it is based on its Partial Euclidean Distance(PED). Depending upon tree pruning strategy the algorithm achieve optimal BER.