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20 August 1998 Iterative joint detection and decoding for MA communications using decision feedback
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Current multiple access communications technology must overcome several key contributors to multi-user interference (MUI) before a fully digital battlefield can be realized. One of the common conditions causing high MUI is the so-called near-far scenario due to interfering transmissions from different users of vastly differing received powers. In current commercial and military systems, MUI is dealt with by choosing user transmission waveforms that are nearly orthogonal (e.g. generous spacing in frequency in an FDMA system) and, often, adaptively controlling transmit powers through receiver control messages back to the users. In times of increased demand, these remedies waste scarce bandwidth that could otherwise be used for information transmission. Additionally, oversaturation, a new idea for increasing channel throughput in which interference is deliberate and heavy, has been made possible by the advent of low complexity joint detection. This paper addresses the ability of a communication system to handle transmissions from different sources during times of increased communication through the development of a low complexity joint detection/decoding algorithm designed to accommodate scenarios of high MUI. The proposed detector carefully integrates decision feedback and error correction decoding in three low complexity stages. The first stage performs user-recursive symbol detection and stripping and the second and third stages perform symbol refinement. Unique to this procedure is the advantageous use of power-ordering and interference-equalization. This scheme results in a consistent and significant performance gain relative to the other low complexity decoding/detection procedures proposed in recent literature. Empirical analysis for various realistic MUI conditions via simulation confirms performance predictions.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rachel E. Learned and Andrew C. Singer "Iterative joint detection and decoding for MA communications using decision feedback", Proc. SPIE 3393, Digitization of the Battlespace III, (20 August 1998);

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