DocumentCode :
3600876
Title :
Joint Design of Pilot Power and Pilot Pattern for Sparse Cognitive Radio Systems
Author :
Chenhao Qi ; Lenan Wu ; Yongming Huang ; Nallanathan, A.
Author_Institution :
Sch. of Inf. Sci. & Eng., Southeast Univ., Nanjing, China
Volume :
64
Issue :
11
fYear :
2015
Firstpage :
5384
Lastpage :
5390
Abstract :
Existing works design the pilot pattern for sparse channel estimation, assuming that the power of all pilots is equal. However, equal power allocation is not optimal in cognitive radio (CR) systems. In this correspondence, we jointly design the pilot power and pilot pattern for sparse channel estimation in orthogonal-frequency-division-multiplexing-based CR systems, based on the rule of mutual incoherence property that minimizes the coherence of the measurement matrix used for the sparse recovery. Under the sum power constraint and peak power constraint, the pilot design is formulated as a joint optimization problem, which is then decoupled into tractable sequential formations. Given a pilot pattern, we formulate the design of pilot power as a second-order cone programming. Then, we propose a joint design algorithm, which includes discrete optimization for pilot pattern and continuous optimization for pilot power. Simulation results show that the proposed algorithm can achieve better channel estimation performance in terms of mean square error and bit error rate and can further improve the spectrum efficiency by 2.4%, compared with existing algorithms assuming equal pilot power.
Keywords :
OFDM modulation; channel estimation; cognitive radio; error statistics; mean square error methods; minimisation; sparse matrices; bit error rate; continuous optimization; discrete optimization; joint optimization problem; mean square error rate; measurement matrix coherence minimization; mutual incoherence property; orthogonal frequency division multiplexing-based CR system; peak power constraint; pilot pattern design; pilot power design; power allocation; second-order cone programming; sparse channel estimation; sparse cognitive radio system; sparse recovery; spectrum efficiency improvement; sum power constraint; Algorithm design and analysis; Channel estimation; Complexity theory; Joints; Optimization; Resource management; Vectors; Cognitive radio (CR); OFDM; compressed sensing (CS); compressed sensing(CS); orthogonal frequency-division multiplexing (OFDM); pilot design; sparse channel estimation;
fLanguage :
English
Journal_Title :
Vehicular Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9545
Type :
jour
DOI :
10.1109/TVT.2014.2374692
Filename :
6966783
Link To Document :
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