Abstract
We propose a method for blind multiuser detection (MUD) in synchronous systems over flat and fast Rayleigh fading channels. We adopt an autoregressive-moving-average (ARMA) process to model the temporal correlation of the channels. Based on the ARMA process, we propose a novel time-observation state-space model (TOSSM) that describes the dynamics of the addressed multiuser system. The TOSSM allows an MUD with natural blending of low-complexity particle filtering (PF) and mixture Kalman filtering (for channel estimation). We further propose to use a more efficient PF algorithm known as the stochastic M -algorithm (SMA), which, although having lower complexity than the generic PF implementation, maintains comparable performance.
Highlights
When multiuser detection (MUD) was introduced in the eighties, it has received a great deal of attention due to its ability to reduce multiple access interference (MAI) and potential for increasing the capacity of CDMA systems
Comparing the Particle filtering detector (PFD) and the Stochastic M detector (SMD) with the decision-directed algorithm, we see that the processes along each trajectory is almost as identical as a decision-directed algorithm except that a sampling step is used in the place of the detection step, and they all resemble one run of Kalman filter which corresponds to a path in the tree of Figure 2
The bit error rate (BER) performance of the proposed PFDs and SMDs are studied through experiments
Summary
When multiuser detection (MUD) was introduced in the eighties, it has received a great deal of attention due to its ability to reduce multiple access interference (MAI) and potential for increasing the capacity of CDMA systems. Numerous detectors have been proposed in the literature for both synchronous and asynchronous transmission. Blind MUD methods are bandwidth more efficient and the approaches proposed, to name a few, include the recursive least square (RLS) [4, 5], subspace-based [6], expectationmaximization [7], genetic algorithm [8] and Kalman filtering [9, 10, 11, 12, 13, 14]. Most of the approaches cited above assume slow or quasi-static fading channels
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