Improved parallel interference cancellation for CDMA

Abstract

This paper introduces an improved nonlinear parallel interference cancellation scheme for code-division multiple access (CDMA) that significantly reduces the degrading effect on the desired user of interference from the other users that share the channel. The implementation complexity of the scheme is linear in the number of users and operates on the fact that parallel processing simultaneously removes from each user a part of the interference produced by the remaining users accessing the channel the amount being proportional to their reliability. The parallel processing can be done in multiple stages. The proposed scheme uses tentative decision devices at the multiple stages to produce the most reliably estimated received data for generation and cancellation of user interference. Simulation results are given for a multitude of different situations, in particular, those cases for which the analysis is too complex.

Effects of Training Parameters on Neural Network Parallel Interference Canceller for CDMA

“…The software programs were relied for simulating the multiuser environment required for CDMA system. This is emphasized in the classic paper of Darius Divsalar on improved parallel interference cancellation for CDMA [7]. This paper closely follows the above paper and [8].…”

Performance Evaluation of a Multi-band UWB Location and Communication System Based on Modified Gegenbauer Functions

“…The matched filter receiver is not optimal in the scope of multi-user communications. More involved systems (multi-user receivers) may be developped to lower the BER, like in CDMA communications or, alternatively, error control codes may be developed [19][20][21]. Another key point is the Doppler effect which may be encountered in practice in our multi-band (that is multi-carrier) system.…”

“…The BER has been computed from equation (17), using the cross-correlation expression (21), for different SNR values and several values of parameter β (which controls the MGF waveshapes, as described in section 2). The results obtained for SNR = 10 dB and β = 1 are shown in the following figures, where the parameter M is kept lower than 2.4 (which corresponds to ∆f = 120MHz with the value chosen for T ).…”

Iterative joint detection using recursive signal cancellation

“…However, whereas tanh(λ k,l /2) = E [d k,l |r k ] is the exact conditional expectation of a given transmitted symbol derived from the LLR ratio of a symbol, tanh(d k,l ) in the FEC-free loop has no such direct interpretation, and is an ad hoc measure that takes note of the fact that d k,l ∈ (±1). The performance of this non-linearity in the feedback loop has not been explored in much detail, but a certain improvement in performance has been observed [25], [13], [9].…”