Iterative Minimum Bit Error Rate Multiuser Detection in Multiple Antenna Aided OFDM

Abstract

A novel iterative Multiuser Detector (MUD) is proposed for employment in Space Division Multiple Access (SDMA) aided Orthogonal Frequency Division Multiplexing (OFDM) systems, where the uplink transmissions of the users share the same bandwidth. The individual users’ signals are differentiated with the aid of their unique user-specific Channel Impulse Responses (CIRs). The MUD commences its operation on a subcarrier by subcarrier basis from the Minimum Mean Square Error (MMSE) MUD antenna array weight vector and invokes the Conjugate Gradient (CG) algorithm for the sake of iteratively adjusting the array weight vector in the direction of the MUD’s true Minimum Bit Error Rate (MBER) solution. Recursive Systematic Convolutional (RSC) codes are used for enhancing the system’s attainable BER performance, which exchange extrinsic information with the MBER MUD for the sake of achieving a turbo-detection aided iteration gain,resulting in the creation of a powerful turbo MBER MUD for employment in multiuser SDMA OFDM systems. The novel benefit of the proposed system is that it is capable of supporting up to a factor two higher number of users than the number of receiver antennas. Explicitly, the technique advocated outperforms other SDMA MUDs with the advent of its MBER optimization criterion and turbo detection structure. Up to 2dBs of iteration gains are attained.

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Identifiers

ORCID for L. Hanzo: orcid.org/0000-0002-2636-5214

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