DocumentCode
2647425
Title
High-SNR analysis of optimum multiuser detection with an unknown number of users
Author
Campo, Adrià Tauste ; Fàbregas, Albert Guillén I ; Biglieri, Ezio
Author_Institution
Dept. of Eng., Univ. of Cambridge, Cambridge, UK
fYear
2009
fDate
11-16 Oct. 2009
Firstpage
283
Lastpage
287
Abstract
We analyze multiuser detection under the assumption that the number of users accessing the channel is unknown by the receiver. Our main goal is to determine the performance loss caused by the need for estimating the identities of active users, which are not known a priori. To prevent a loss of optimality, we assume that identities and data are estimated jointly, rather than in two separate steps. We examine the performance of multiuser detectors when the number of potential users is large. Statistical-physics methodologies are used to determine the fixed-point equation whose solutions yield the multiuser efficiency of the optimal detector. Special attention is paid to the large signal-to-noise ratio, which yields tight closed-form bounds on the minimum mean-squared error. These bounds analytically illustrate the set of solutions of the fixed-point equation, and their relationship with the maximum system load. By identifying the region of computationally feasible solutions, we study the maximum load that the detector can support for a given SNR and quality of service, specified by the multiuser efficiency.
Keywords
code division multiple access; least mean squares methods; multiuser detection; closed-form bounds; fixed-point equation; minimum mean-squared error; optimum multiuser detection; statistical-physics methodologies; Conferences; Detectors; Equations; Error analysis; Information analysis; Information theory; Multiaccess communication; Multiuser detection; Performance loss; Signal to noise ratio;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Workshop, 2009. ITW 2009. IEEE
Conference_Location
Taormina
Print_ISBN
978-1-4244-4982-8
Electronic_ISBN
978-1-4244-4983-5
Type
conf
DOI
10.1109/ITW.2009.5351171
Filename
5351171
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