Cooperative Demodulation by Link Adaptive Relaying
Publish place: 19th Iranian Conference on Electric Engineering
Publish Year: 1390
نوع سند: مقاله کنفرانسی
زبان: English
View: 1,115
This Paper With 5 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICEE19_466
تاریخ نمایه سازی: 14 مرداد 1391
Abstract:
In cooperative communication systems, the decodeand- forward (DF) relaying is a practically attractive strategy. Existing techniques for mitigating the error propagation in this scheme can be classified into two groups: the first of these uses link SNRs to evaluate the reliability of the data received by the relay and the second approach is to develop better combining schemes at the destination. In this paper, a combination of both methods has been proposed. The purpose of this work is obtaining performance gain by the degree of freedom in the relay. So the power scaling coefficients in the relay are proposed that give a better performance in comparison with Cooperative MRC (C-MRC). Also a suitable combiner is used in the destination that is a generalization of C-MRC and is an approximation of ML detector. We show the advantage of the new proposed scheme through simulations and analytical analysis in which the coding gain is utilized as a performance metric to compare cooperative detectors. A power scaling coefficient in the relay is proposed that is independent of instantaneous SNR at source-relay link and has a surprising gain when the relay is located close to the source. It is demonstrated that in high SNRs, the average BER of the new relaying scheme with this coefficient almost achieves a lower bound.
Keywords:
Cooperative networks , decode-and-forward relaying , link adaptive relaying , maximum-ratio-combining , coding gain , bit error rate (BER
Authors
Mostafa Azhini
Signal Processing and Communication Systems Laboratory, School of Electrical and Computer Engineering,University of Tehran, Tehran, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :