Energy Efficiency Optimization for OFDM-Based Cognitive Radio Systems: A Water-Filling Factor Aided Search Method

Mao, Junling; Xie, Gang; Gao, Jinchun; Liu, Yuanan

doi:10.1109/twc.2013.013013.121013

Cited by 77 publications

(58 citation statements)

References 27 publications

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“…This is defined as the instantaneous transmission rate (or throughput) divided by the instantaneous transmit and consumed circuitry power (or energy), and is expressed in bits/joule (bits/J) [10,12,25,34,35,44,45,49].…”

Section: Energy Efficiency (Ee) Metricsmentioning

confidence: 99%

“…For instance, for multicarrier communication systems, if a single SU employs an orthogonal frequency division multiplexing (OFDM) in order to access the available spectrum, the instantaneous EE is defined as [35,45] …”

Section: Energy Efficiency (Ee) Metricsmentioning

confidence: 99%

“…In such a case, transmit power [1,27,34,35,40,45], signal-to-interference-plus-noise ratio (SINR) threshold [22], frequency bands/subcarriers [9,25,44,49], and/or packet length [38] are optimized separately or jointly in order to improve the CR system energy efficiency.…”

Section: Sensing-less Energy-aware Resource Allocationmentioning

confidence: 99%

“…Towards a more practical scenario where the SU coexists with multiple PUs in the overlay approach and guarantees certain QoS requirements, a minimum supported rate is added to the optimization problem [35]. A novel method, namely the generalized waterfilling factor aided search (WFAS), is proposed to solve the nonconvex optimization problem [35].…”

Section: Power Allocation Of Multicarrier Systemsmentioning

confidence: 99%

“…A novel method, namely the generalized waterfilling factor aided search (WFAS), is proposed to solve the nonconvex optimization problem [35]. A simplified version of the WFAS method is further presented.…”

Section: Power Allocation Of Multicarrier Systemsmentioning

confidence: 99%

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Energy-Aware Cognitive Radio Systems

Bedeer

Amin

Dobre

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Energy Management in Wireless Cellular and Ad-Hoc Networks

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The concept of energy-aware communications has spurred the interest of the research community in the most recent years due to various environmental and economical reasons. It becomes indispensable for wireless communication systems to shift their resource allocation problems from optimizing traditional metrics, such as throughput and latency, to an environmental-friendly energy metric. Although cognitive radio systems introduce spectrum efficient usage techniques, they employ new complex technologies for spectrum sensing and sharing that consume extra energy to compensate for overhead and feedback costs. Considering an adequate energy efficiency metric-that takes into account the transmit power consumption, circuitry power, and signaling overhead-is of momentous importance such that optimal resource allocations in cognitive radio systems reduce the energy consumption. A literature survey of recent energy-efficient based resource allocations schemes is presented for cognitive radio systems. The energy efficiency performances of these schemes are analyzed and evaluated under power budget, co-channel and adjacentchannel interferences, channel estimation errors, quality-of-service, and/or fairness constraints. Finally, the opportunities and challenges of energy-aware design for cognitive radio systems are discussed.

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