標題: Blind adaptive energy estimation for decorrelating decision-feedback CDMA multiuser detection using learning-type stochastic approximations
作者: Chang, PR
Lee, CC
Lin, CF
電信工程研究所
Institute of Communications Engineering
關鍵字: CDMA;DDF multiuser detection;stochastic approximation
公開日期: 1-Mar-1999
摘要: This paper investigates the application of linear reinforcement learning stochastic approximation to the blind adaptive energy estimation for a decorrelating decision-feedback (DDF) multiuser detector over synchronous code-division multiple-access (CDMA) radio channels in the presence of multiple-access interference (MAI) and additive Gaussian noise. The decision feedback incorporated into the structure of a linear decorrelating detector is able to significantly improve the weaker users' performance by canceling the MAI from the stronger users. However, the DDF receiver requires the knowledge of the received energies, In this paper, a new novel blind estimation mechanism is proposed to estimate all the users' energies using a stochastic approximation algorithm without training data. In order to increase the convergence speed of the energy estimation, a linear reinforcement learning technique is conducted to accelerate the stochastic approximation algorithms. Results show that our blind adaptation mechanism is able to accurately estimate an the users' energies even if the users of the DDF detector are not ranked properly. After performing the blind energy estimation and then reordering the users in a nonincreasing order, numerical simulations show that the DDP detector for the weakest user performs closely to the maximum likelihood detector, whose complexity grows exponentially with the number of users.
URI: http://dx.doi.org/10.1109/25.752579
http://hdl.handle.net/11536/31467
ISSN: 0018-9545
DOI: 10.1109/25.752579
期刊: IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume: 48
Issue: 2
起始頁: 542
結束頁: 552
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