Minimum PED based K best algorithm for high performance MIMO detector

Minimum Partial Euclidean Distance (PED) based K best algorithm is proposed. It is based on breath first search methods. The proposed design is independent of the constellation size, number of transmit and receive antenna. The minimum PED based K best detector guarantees a Signal to Noise Ratio (SNR)-independent fixed throughput with a performance close to Maximum Likelihood Detection (MLD) method and reduced Bit Error Rate (BER) with irrespective of constellations. The main innovations are the nodes are expanded and visited based on minimum parent PED rather than exhaustively, as well as it keeps track of symbols selected at each cycle. Being fixed-throughput in nature along with the fact that the breadth first approaches are feed forward detection schemes makes them especially attractive one for VLSI implementation. The simulation is carried out in different stages, in this paper the number of transmit and receive antennas is chosen as 2 and 64 constellations QAM is chosen. The received signal from MIMO transmitter is detected using the minimum PED based K best algorithm, Moreover, the algorithm builds a tree with the children´s and identify the best child with minimum PED, the selected child act as an parent node for next cycle and the cycle is repeated until all such children´s in a tree are visited, Finally the scatter plot is plotted for both Rayleigh channel and Additive white Gaussian noise channel (AWGN). The calculation for SNR vs. BER shows the AWGN channel provides the less amount of bit error involved in signal compared to Rayleigh channel scheme with the proposed algorithm.