Download Cognitive Radio Networks: Dynamic Resource Allocation by Shaowei Wang PDF

By Shaowei Wang

ISBN-10: 3319089358

ISBN-13: 9783319089355

ISBN-10: 3319089366

ISBN-13: 9783319089362

This SpringerBrief provides a survey of dynamic source allocation schemes in Cognitive Radio (CR) platforms, concentrating on the spectral-efficiency and energy-efficiency in instant networks. It additionally introduces various dynamic source allocation schemes for CR networks and gives a concise advent of the panorama of CR know-how. the writer covers intimately the dynamic source allocation challenge for the motivations and demanding situations in CR platforms. The Spectral- and Energy-Efficient source allocation schemes are comprehensively investigated, together with new insights into the trade-offs for working concepts. Promising examine instructions on dynamic source administration for CR and the purposes in different instant verbal exchange structures also are mentioned. Cognitive Radio Networks: Dynamic source Allocation Schemes goals laptop scientists and engineers operating in instant communications. Advanced-level scholars in desktop technology and electric engineering also will locate this short necessary studying concerning the subsequent new release of instant communication.

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Song and Y. G. Li, “Utility-based joint physical-MAC layer optimization in OFDM,” in Proc.  671–675, Nov. 2002. 31. G. Song and Y. G. Li, “Adaptive subcarrier and power allocation in OFDM based on maximizing utility,” in Proc.  905–909, Apr. 2003. 32. M. -C. Liang, and F. Zhang, “Resource allocation for delay differentiated traffic in multiuser OFDM systems,” IEEE Trans.  2190–2201, June 2008. 33. C. Xiong, G. Y. Li, S. Zhang, Y. Chen, S. Xu, “Energy-Efficient Resource Allocation in OFDMA Networks,” in Proc.

1007/978-3-319-08936-2_3 27 28 3 Spectral-Efficient Resource Allocation in CR Systems Fig. 1 Channel model for primary/secondary network with single SU which can be regarded as noise and measured by the receiver of an SU. Thus, the SNR of the nth subchannel with unit power is 2 Hn = hn , W PS N0 + I n N where N0 is the PSD of the additive white Gaussian noise and hn is the channel gain from the CR AP to the receiver of the SU. The achievable rate of the CR system can be calculated by pH  W  log 2 1 + n n  ,  Γ  n =1 N N R=∑ where Γ represents the SNR gap and we can take Γ = − MQAM with a specified BER.

Thus, the SNR of the nth subchannel with unit power is 2 Hn = hn , W PS N0 + I n N where N0 is the PSD of the additive white Gaussian noise and hn is the channel gain from the CR AP to the receiver of the SU. The achievable rate of the CR system can be calculated by pH  W  log 2 1 + n n  ,  Γ  n =1 N N R=∑ where Γ represents the SNR gap and we can take Γ = − MQAM with a specified BER. 2 Problem Formulation We expect to maximize the SE of the CR network, while the interference introduced to each PU band should be controlled below a given threshold prescribed by the interference temperature.

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