Title :
Primary User Traffic Classification in Dynamic Spectrum Access Networks
Author :
Chun-Hao Liu ; Pawelczak, Przemyslaw ; Cabric, Danijela
Author_Institution :
Dept. of Electr. Eng., Univ. of California, Los Angeles, Los Angeles, CA, USA
Abstract :
This paper focuses on analytical studies of the primary user (PU) traffic classification problem. colorblack{Observing} that the gamma distribution can represent positively skewed data and exponential distribution (popular in communication networks performance analysis literature) it is considered here as the PU traffic descriptor. We investigate two PU traffic classifiers utilizing perfectly measured PU activity (busy) and inactivity (idle) periods: (i) maximum likelihood classifier (MLC) and (ii) multi-hypothesis sequential probability ratio test classifier (MSPRTC). Then, relaxing the assumption on perfect period measurement, we consider a PU traffic observation through channel sampling. For a special case of negligible probability of PU state change in between two samplings, we propose a minimum variance PU busy/idle period length estimator. Later, relaxing the assumption of the complete knowledge of the parameters of the PU period length distribution, we propose two PU traffic classification schemes: (i) estimate-then-classify (ETC), and (ii) average likelihood function (ALF) classifiers considering time domain fluctuation of the PU traffic parameters. Numerical results show that both MLC and MSPRTC are sensitive to the periods measurement errors when the distance among distribution hypotheses is small, and to the distribution parameter estimation errors when the distance among hypotheses is large. For PU traffic parameters with a partial prior knowledge of the distribution, the ETC outperforms ALF when the distance among hypotheses is small, while the opposite holds when the distance is large.
Keywords :
exponential distribution; gamma distribution; maximum likelihood estimation; parameter estimation; radio spectrum management; sampling methods; subscriber loops; telecommunication traffic; time-domain analysis; wireless channels; ALF classifier; ETC; MLC; MSPRTC; PU traffic classification; average likelihood function classifier; channel sampling; distribution parameter estimation error; dynamic spectrum access network; estimate-then-classify; exponential distribution; gamma distribution; maximum likelihood classifier; minimum variance PU busy-idle period length estimator; multihypothesis sequential probability ratio test classifier; primary user traffic classification; time domain fluctuation; Analytical models; Estimation error; Noise measurement; Probability density function; Random variables; Sensors; Dynamic spectrum access; performance analysis; traffic classification; traffic estimation; traffic sampling;
Journal_Title :
Selected Areas in Communications, IEEE Journal on
DOI :
10.1109/JSAC.2014.141122