TY - JOUR
T1 - Stochastic-Geometry Based Characterization of Aggregate Interference in TVWS Cognitive Radio Networks
AU - Deshmukh, Madhukar Mohanrao
AU - Zafaruddin, S. M.
AU - Mihovska, Albena
AU - Prasad, Ramjee
N1 - Publisher Copyright:
© 2007-2012 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - In this paper, we characterize the worst-case interference for a finite-area TV white space heterogeneous network using the tools of stochastic geometry. We derive closed-form expressions on the probability distribution function (PDF) and an average value of the aggregate interference for various values of path loss exponent under Rayleigh fading channel. The proposed characterization of the interference is simple and can be used in improving the spectrum access techniques. Using the derived PDF, we demonstrate the performance gain in the spectrum detection of an eigenvalue-based detector for cognitive radio networks.
AB - In this paper, we characterize the worst-case interference for a finite-area TV white space heterogeneous network using the tools of stochastic geometry. We derive closed-form expressions on the probability distribution function (PDF) and an average value of the aggregate interference for various values of path loss exponent under Rayleigh fading channel. The proposed characterization of the interference is simple and can be used in improving the spectrum access techniques. Using the derived PDF, we demonstrate the performance gain in the spectrum detection of an eigenvalue-based detector for cognitive radio networks.
KW - Aggregate interference
KW - cognitive radio (CR)
KW - stochastic geometry
KW - television white space (TVWS)
UR - https://www.scopus.com/pages/publications/85071631434
U2 - 10.1109/JSYST.2019.2904584
DO - 10.1109/JSYST.2019.2904584
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AN - SCOPUS:85071631434
SN - 1932-8184
VL - 13
SP - 2728
EP - 2731
JO - IEEE Systems Journal
JF - IEEE Systems Journal
IS - 3
M1 - 8678398
ER -