By introducing the bit-level multi-stream coded Layered Space-Time(LST) transmitter along with a novel iterative MultiStage Decoding(MSD) at the receiver,the paper shows how to achieve the near-capacity performance of the Multiple-Input Multiple-Output(MIMO) systems with square Quadrature Amplitude Modulation(QAM) . In the proposed iterative MSD scheme,the detection at each stage is equivalent to multiuser detection of synchronous Code Division Multiple Access(CDMA) multiuser systems with the aid of the binary representation of the transmitted symbols. Therefore,the optimal Soft-Input Soft-Output(SISO) multiuser detection and low-complexity SISO multiuser detection can be utilized herein. And the proposed scheme with low-complexity SISO multiuser detection has polynomial complexity in the number of transmit antennas M,the number of receive antennas N,and the number of bits per constellation point Mc. Simulation results demonstrate that the proposed scheme has similar Bit Error Rate(BER) performance to that of the known Iterative Tree Search(ITS) detection.
Recently, network coding has been applied to the loss recovery of reliable broadcast transmission in wireless networks. Since it was proved that fi nding the optimal set of lost packets for XOR-ing is a complex NP-complete problem, the available time-based retransmission scheme and its enhanced retransmission scheme have exponential computational complexity and thus are not scalable to large networks. In this paper, we present an efficient heuristic scheme based on hypergraph coloring and also its enhanced heuristic scheme to improve the transmission efficiency. Basically, our proposed schemes fi rst create a hypergraph according to the packet-loss matrix. Then our schemes solve the problem of generating XORed packets by coloring the edges of hypergraph. Extensive simulation results demonstrate that, the heuristic scheme based on hypergraph coloring and its enhanced scheme can achieve almost the same transmission efficiency as the available ones, but have much lower computational complexity, which is very important for the wireless devices without high computation capacity.
