SPC11-5: Joint Transceiver Optimization in MC-CDMA Systems Exploiting Multipath and Spatial Diversity

Seo, Kyoungnam; Yang, Liuqing

doi:10.1109/glocom.2006.595

Cited by 1 publication

(1 citation statement)

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“…Several optimization methods in CDMA and MC-CDMA systems are reported in literature that include adaptive algorithm to minimize the total transmitted power [3], signalto-interference ratio (SIR) balanced optimum power control in CDMA [4], joint optimization of spreading codes and a utility based power control [5], joint rate and power control [6], joint transmitter-receiver optimization using multiuser detection and resource allocation for energy efficiency in wireless CDMA networks [7], using transmitter power control, receiver array processing and multiuser detection [8], etc. However, none of the works consider PAPR (intrinsic in multicarrier) and MAI (intrinsic in CDMA) effect together in their optimization problems.…”

Section: Introductionmentioning

confidence: 99%

On optimization of CI/MC-CDMA system

Maity

Mukherjee

2009

2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications

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This paper proposes a new model of high capacity carrier interferometry/multicarrier code division multiple access (CI/MCCDMA) system through the simultaneous support of high and low data rate transmission using odd and even subcarriers. Reduction in peak-to-average power ratio (PAPR) is achieved through the phase shift of even (odd) CI code using odd (even) sub-carriers by an amount of π/2 and odd (even) CI code using odd (even) sub-carriers by -π/2, all angles measured with respect to the orthogonal codes supporting high data rate transmission. The CI code optimization is done for further reduction in PAPR values. Specifically, assuming a frequency selective Rayleigh-fading channel, bit error rate (BER) at receiver is improved through the cancelation of MAI (multiple access interference) at subcarriers level using PIC (parallel interference cancelation) at reduced computation cost. Finally, the system is optimized with respect to the number of subcarriers, number of users (capacity) and signal-to-noise ratio (SNR) using GAs (Genetic Algorithms) to achieve an acceptable set of values for BER, PAPR and average data rate (ADR).

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