Minimum Partial Euclidean
Distance (MPED) based K-best algorithm is proposed to detect the best signal
for MIMO (Multiple Input Multiple Output) detector. It is based on
Breadth-first search method. The proposed algorithm is independent of the
number of transmitting/receiving antennas and constellation size. It provides a
high throughput and reduced Bit Error Rate (BER) with the performance close to
Maximum Likelihood Detection (MLD) method. The main innovations are the nodes
that are expanded and visited based on MPED algorithm and it keeps track of
finally selecting the best candidates at each cycle. It allows its complexity
to scale linearly with the modulation order. Using Quadrature Amplitude
Modulation (QAM) the complex domain input signals are modulated and are
converted into wavelet packets and these packets are transmitted using Additive
White Gaussian Noise (AWGN) channel. Then from the number of received signals
the best signal is detected using MPED based K-best algorithm. It provides the
exact best node solution with reduced complexity. The pipelined VLSI
architecture is the best suited for implementation because the expansion and
sorting cores are data driven.？The
proposed method is implemented targeting Xilinx Virtex 5 device for a 4？×？4,
64-QAM system and it achieves throughput of 1.1 Gbps. The results of resource
utilization are tabulated and compared with the existing algorithms.
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