A Discrete Artificial Bee Colony (DABC) is presented for joint symbol detection at the receiver in a multidevice Space-Time Block\r\nCode (STBC) Mutli-Input Multi-Output (MIMO) communication system. Exhaustive search (maximum likelihood detection)\r\nfor finding an optimal detection has a computational complexity that increases exponentially with the number of mobile\r\ndevices, transmit antennas per mobile device, and the number of bits per symbol. ABC is a new population-based, swarm-based\r\nEvolutionary Algorithms (EA) presented for multivariable numerical functions and has shown good performance compared to\r\nother mainstream EAs for problems in continuous domain. This algorithm simulates the intelligent foraging behavior of honeybee\r\nswarms. An enhanced discrete version of the ABC algorithm is presented and applied to the joint symbol detection problem to find\r\na nearly optimal solution in real time. The results of multiple independent simulation runs indicate the effectiveness of DABC\r\nwith other well-known algorithms previously proposed for joint symbol detection such as the near-optimal sphere decoding,\r\nminimum mean square error, zero forcing, and semidefinite relaxation, along with other EAs such as genetic algorithm, estimation\r\nof distributions algorithm, and the more novel biogeography-based optimization algorithm.
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