A Low-Complexity High-Performance Preprocessing Algorithm for Multiuser Detection using Gold Sequences
| Autor: | Axehill, Daniel, Hansson, Anders, Gunnarsson, Fredrik |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2008 |
| Předmět: |
Suboptimal detector
Gold sequences Time-synchronous users Successive interference cancellation Multiuser detection Optimal detector TEKNIKVETENSKAP Quadratic programming Optimum multiuser detection problem Code division multiple access Sequences Low-complexity high-performance preprocessing algorithm Maximum likelihood problem Computational complexity CDMA channel models Bit error rate Binary quadratic programming problem Low cross correlation Interference suppression TECHNOLOGY Error statistics NP-hard problem Maximum likelihood detection Parallel interference cancellation |
| Popis: | The optimum multiuser detection problem can be formulated as a maximum likelihood problem, which yields a binary quadratic programming problem to be solved. Generally this problem is NP-hard and is therefore hard to solve in real time. In this paper, a preprocessing algorithm is presented which makes it possible to detect some or all users optimally for a low computational cost if signature sequences with low cross correlation, e.g., Gold sequences, are used. The algorithm can be interpreted as, e.g., an adaptive tradeoff between parallel interference cancellation and successive interference cancellation. Simulations show that the preprocessing algorithm is able to optimally compute more than 94,% of the bits in the problem when the users are time-synchronous, even though the system is heavily loaded and affected by noise. Any remaining bits, not computed by the preprocessing algorithm, can either be computed by a suboptimal detector or an optimal detector. Simulations of the time-synchronous case show that if a suboptimal detector is chosen, the bit error rate (BER) rate is significantly reduced compared with using the suboptimal detector alone. |
| Databáze: | OpenAIRE |
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