Comment on "Energy detection of unknown deterministic signals"

Abstract

INPUT Bo 70i ! "t ,i * 20 40 €a 80 1 0 0 120 1 4 0 $ 6 0 FRMUENCY Hz Fig. 3. Measured and theoretical frequency Rspons of ZGo).(The Q of the response is indicative of the proximity of the poles to the axis.) It should be noted that this particular realization may be unstable due to the large open loop gain at high frequencies. Careful desigq using conventional Bode techniques, can ensure stability by the addition of a "roll-off" capacitor C, as shown in Fig. qa). The measured response, given in Fig. 3, agrees closely with (4). The Q of this response is approximately 20 and is limited by the h i t e gain and nonzero phase shift of the transistors.The applications of this type of network are the subject of continuing work. Preliminary investigations have indicated that the problem of simulating floating inductors in low-pass LC ladder filters may be overcome by replacing the floating inductors by resistors and the shunt capacitors by impedances of the type given in (3). hactical circuit realizations, using this method, are being investigated and it will be shown that many LC driving point and transfer immittances may be simulated. The results of this work will be reported at a later date.

A new mathematical analysis of the probability of detection in cognitive radio over fading channels

“…At a low value ofγ , i.e.,γ = −10 dB, it can be seen that increasing the value of m, (m = 1, 2, 3), does not improve the misdetection probability for both derived expressions which concurs with the numerical integration of (18). We also note that (29) exactly matches (18); on the other hand, there is a minor discrepancy between (27) and (18).…”

“…The derived expressions are evaluated and compared with the numerical integration of (18) and with the expressions reported by [14][15][16][17] In the odd case, the simulation is compared to the recursive formula (13,16) in AWGC, and in the even case, the simulation is compared to (10) in AWGC and to ( [14], Eq. 14).…”

“…The existence or absence of a PU signal can be modeled as a binary hypotheses problem as originally proposed by [18,19] and later followed by most researchers [20,21]. This model differentiates between two hypotheses defined as:…”

Adaptive Algorithms for Bayesian Spectrum Sensing Based on Markov Model

“…There are several classical spectrum sensing (SS) methods, such as matched filter detection [5], cyclostationary feature detection [6] and energy detection (ED) [7]. Among them, ED is the simplest and the most popular SS mechanism since it does not require prior information about PU signals [8][9]. In [10][11][12], some cooperative PU detection approaches are suggested to exploit the diversity of multiple SUs.…”

Signal detection in cognitive radio networks over AWGN, Nakagami-m and Nakagami-q channels

“…The output of the integrator, represented by the decision statistic Y , is compared to a predetermined threshold γ to determine the presence (H 1 ) or absence (H 0 ) of a PU. The presence or absence of a PU signal can be modeled as binary hypotheses problem as originally proposed by [7], [15] and latter followed by most researchers [16], 17]. The received signal samples under two hypotheses defined as:…”