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RISS 인기검색어
- 검색키워드
- 저자 : ( Aymen M. Kareem ) (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
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Combined Time Synchronization And Channel Estimation For MB-OFDM UWB Systems
( Aymen M. Kareem ),( Ayman A. El-saleh ),( Masuri Othman ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.7
Symbol timing error amounts to a major degradation in the system performance. Conventionally, timing error is estimated by predefined preamble on both transmitter and receiver. The maximum of the correlation result is considered the start of the OFDM symbol. Problem arises when the prime path is not the strongest one. In this paper, we propose a new combined time and channel estimation method for multi-band OFDM ultra wide-band (MB-OFDM UWB) systems. It is assumed that a coarse timing has been obtained at a stage before the proposed scheme. Based on the coarse timing, search interval is set (or time candidates). Exploiting channel statistics that are assumed to be known by the receiver, we derive a maximum a posteriori estimate (MAP) of the channel impulse response. Based on this estimate, we discern for the timing error. Timing estimation performance is compared with the least squares (LS) channel estimate in terms of mean squared error (MSE). It is shown that the proposed timing scheme is lower in MSE than the LS method.
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Minimizing Sensing Decision Error in Cognitive Radio Networks using Evolutionary Algorithms
( Mohsen Akbari ),( Md. Kamal Hossain ),( Mohsen Riahi Manesh ),( Ayman A. El-saleh ),( Aymen M. Kareem ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.9
Cognitive radio (CR) is envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, the main concern is to reliably sense the presence of primary users (PUs) to attain protection against harmful interference caused by potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA) are proposed to minimize the total sensing decision error at the common soft data fusion (SDF) centre of a structurally-centralized cognitive radio network (CRN). Using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed methods are compared with each other as well as with other conventional deterministic algorithms such as maximal ratio combining (MRC) and equal gain combining (EGC). Computer simulations confirm the superiority of the PSO-based scheme over the GA-based and other conventional MRC and EGC schemes in terms of detection performance. In addition, the PSO-based scheme also shows promising convergence performance as compared to the GA-based scheme. This makes PSO an adequate solution to meet real-time requirements.
ScienceON
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