Resource allocation in FBMC-based two-cell cognitive radio systems with estimated CSI

Lv, Hengwei; Li, Pandong; Zhang, Haijian; Qian, Yongqing

doi:10.1109/icsp.2016.7878037

Cited by 1 publication

(2 citation statements)

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“…An interference-limited method was presented in [19], where the co-channel interference is assumed to be constant and then transformed into a constraint. In [20,21], the non-cooperative game theory was adopted to solve the problem of multi-cell, and Nash equilibrium is guaranteed. However, less efforts have been devoted to the research of the energy-efficient multicell resource allocation.…”

Section: Related Workmentioning

confidence: 99%

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Energy-efficient multi-cell resource allocation in cognitive radio-enabled 5G systems

Yan

et al. 2019

EURASIP J. Adv. Signal Process.

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In this paper, we propose an energy-efficient resource allocation (RA) algorithm in cognitive radio-enabled 5th generation (5G) systems, where the scenario including one primary system and multiple secondary cells is considered. Because of the high spectrum leakage of traditional orthogonal frequency division multiplexing (OFDM), alternative modulation schemes regarded as the potential air interfaces in 5G are analyzed, e.g., filter bank-based multi-carrier (FBMC), generalized frequency division multiplexing (GFDM), and universal filtered multi-carrier (UFMC). Our objective is to maximize the whole energy efficiency of secondary system defined by the ratio of the capacity to the total power consumption subject to some practical constraints. The general formulation leads to a non-convex mixed-integer nonlinear programming problem with fractional structure, which is challenging to solve due to its intractability and significant complexity. Therefore, we resort to an alternate optimization framework to optimize the variables of subcarrier assignment and power allocation, where successive convex approximation (SCA) is employed so that the general formulation is finally transformed into a solvable convex problem. Numerical results validate the effectiveness of the proposed RA algorithm, and the comparison with some existing RA algorithms is conducted. In addition, the performance of using different 5G candidate waveforms in the energy-efficient RA algorithm is also presented and discussed.

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Section: Related Workmentioning

confidence: 99%

“…By introducing a logarithmic manipulation P = exp P and bringing it into (21), then the final optimization problem after approximation is formulated as Q4: max…”

Section: Power Allocation Based On Scamentioning

confidence: 99%

Energy-efficient multi-cell resource allocation in cognitive radio-enabled 5G systems

Yan

et al. 2019

EURASIP J. Adv. Signal Process.

Self Cite

View full text Add to dashboard Cite

show abstract

Resource allocation in FBMC-based two-cell cognitive radio systems with estimated CSI

Cited by 1 publication

References 19 publications

Energy-efficient multi-cell resource allocation in cognitive radio-enabled 5G systems

Energy-efficient multi-cell resource allocation in cognitive radio-enabled 5G systems

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