Abstract / Description of output
Code division multiple access (CDMA) spread spectrum systems that employ RAKE receivers for data detection require an estimate of the channel impulse response to be made prior to extracting the data. In a rapidly fading environment, such as that experienced by mobile cellular systems, the application of a prediction algorithm to the problem of estimating the channel impulse response can improve the system performance over a non-predictive one. The paper describes the application of the least squares (LS) prediction algorithm to a RAKE receiver system, and present results obtained through Monte-Carlo simulation. The LS algorithm is computed using a computationally efficient sliding FFT based approach based on radix 4 butterflies. A novel prediction feedback method, called conditional decision feedback, for reducing the effect of decision feedback errors is presented. A typical urban environment was selected to evaluate the system performance, the COST 207 channel model for this environment being used to drive the simulation system
| Original language | English |
|---|---|
| Title of host publication | IEEE International Conference on Communications, 1995 (ICC '95) |
| Pages | 1823-1827 vol.3 |
| Volume | 3 |
| DOIs | |
| Publication status | Published - 1 Jun 1995 |
Keywords / Materials (for Non-textual outputs)
- cellular radio, code division multiple access, fading, fast Fourier transforms, feedback, land mobile radio, least squares approximations, prediction theory, pseudonoise codes, radio receivers, spread spectrum communication, transient responseCOST 207 channel model, LS algorithm, Monte-Carlo simulation, RAKE receiver system, channel impulse response, code division multiple access, conditional decision feedback, data detection, decision feedback errors, generalised sliding FFT algorithm, least squares prediction algorithm, mobile cellular systems, mobile channels, prediction algorithm, prediction feedback method, radix 4 butterflies, rapidly fading environment, simulation system, spread spectrum systems, system performance, urban environment