Soft-input/soft-output multiuser detection for iterative decoding of asynchronous CDMA systems with convolutional codes

Abstract

The optimal decoding scheme for asynchronous code-division multiple access (CDMA) systems that employ convolutional codes results in a prohibitive computational complexity. To reduce computational complexity, iterative receiver structures have been proposed for decoding multiuser data. At each iteration, extrinsic information is exchanged between a soft-input/soft-output (SISO) multiuser detector (MUD) and a bank of single-user SISO channel decoders. For asynchronous cases (see Alexander, P.D. et al., IEEE Trans. Commun., vol.47, p.1008-14, 1999), an optimal SISO MUD was derived based on the chip-synchronous assumption which is in general not valid for asynchronous CDMA systems. We propose an algorithm for an optimal SISO MUD without the chip-synchronous assumption. A direct implementation of the optimal SISO MUD also has exponential computational complexity in terms of the number of users, which is still prohibitive for channels with medium to large numbers of users. A low-complexity SISO MUD is proposed based on the decision-feedback scheme. In it, tentative hard decisions are made and fed back to the SISO multiuser from previously decoded output. The computational complexity of this detector can be linear in terms of the number of users and can be adjusted according to the complexity/performance trade-off. Simulations show that the performance of the low-complexity SISO MUD approaches that of the single-user system for moderate to high signal-to-noise ratios (SNR), even for a large number of users.