DocumentCode :
2185184
Title :
Deep sensing for future 5G communications with mobile primary users
Author :
Li, Bin ; Nan, Yijiang ; Zhao, Chenglin ; Nallanathan, A.
Author_Institution :
School of Information and Communication Engineering (SICE), Beijing University of Posts and Telecommunications (BUPT), 100876, China
fYear :
2015
fDate :
21-24 July 2015
Firstpage :
521
Lastpage :
525
Abstract :
A promising joint estimation paradigm, namely deep sensing, is proposed for more challenging spectrum-location awareness 5G applications. A major innovation of the new sensing algorithm is that the mutual interruption between two unknown quantities, i.e. unknown primary states and its moving locations, is fully considered. A unified system model is formulated relying on the dynamic state-space approach, by taking two coupling hidden states into accounts. A random finite set (RFS) inspired Bayesian algorithm is suggested to estimate unknown PU states recursively accompanying its time-varying locations. To avoid the mis-tracking aroused by the intermittent disappearance of PU, an adaptive horizon expanding (AHE) mechanism is designed. Experiments also validate the proposed scheme.
Keywords :
5G mobile communication; Cognitive radio; Estimation; Heuristic algorithms; Joints; Proposals; Sensors; PU´s location; Spectrum sensing; deep sensing; dynamic state-space model; random finite state;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing (DSP), 2015 IEEE International Conference on
Conference_Location :
Singapore, Singapore
Type :
conf
DOI :
10.1109/ICDSP.2015.7251927
Filename :
7251927
Link To Document :
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