Cooperative Energy Detection With Heterogeneous Sensors Under Noise Uncertainty: SNR Wall and Use of Evidence Theory

Abstract

The analyzed system model in this paper is a distributed parallel detection network in which each secondary user (SU) evaluates the energy-based test statistic from the received observations and sends it to a fusion center (FC), which makes the final decision. Uncertainty in the noise variance at each SU is modeled as an unknown constant in a certain interval around the nominal noise variance. It is assumed that the SUs are heterogeneous in that the nominal noise variances and the uncertainty intervals can be different for different SUs. Moreover, the received signal power at each SU may be different. For the considered system model, the paper presents important results for two interrelated themes on cooperative energy detection (CED) in the presence of noise uncertainty (NU). First, the expressions for generalized SNR walls are derived for the classical CED fusion rule, i.e., sum of energies from all SUs. Second, a Dempster-Shafer theory (DST) based CED is proposed in the presence of NU with heterogeneous sensors. In the proposed scheme, the test statistic from each SU is the energy-based basic mass assignment (BMA) values, which are first discounted depending on the uncertainty level associated with the SU and then fused at the FC using the Dempster rule of combination to arrive at the global decision. It is shown that the proposed scheme outperforms the traditional sum fusion rule in terms of detection performance as well as the location of SNR wall.

On the Signal-to-Noise Ratio Wall of Energy Detection in Spectrum Sensing

“…The SNRw for the GED in AWGN channels is derived, and the independence of the moment of the detector is also demonstrated, possibly causing a reduction in the SNRw as the moment increases, depending on the diversity technique adopted. A generalized SNRw for the ED in CSS under NU is derived in [20], where SUs possibly experience different nominal noise powers, received PU signal powers and NU levels. Results show that the traditional expressions for the SNRw of ED in nCSS and CSS with homogeneous SUs are particular cases of the generalized SNRw of ED with heterogeneous SUs.…”

“…In addition to the above-mentioned, the literature also presents several other related research works considering different circumstances, scenarios, models and distributions of the NU, proposing strategies to increase the detector robustness against NU and decrease the limitations imposed by the SNRw on ED in nCSS and CSS, as can be verified for instance in [20]- [27]. The work in [24], for example, proposes two NU models based on discrete and continuous NU distributions and shows that one can improve the performances of ED without increasing the sensing time by assuming a priori knowledge on the noise distribution and selecting a proper decision threshold.…”

Double Threshold Weighted Energy Detection for Asynchronous PU Activities in the Presence of Noise Uncertainty

“…In a cooperative spectrum sensing approach, the uncertainty problem can be mitigated by exploiting the spatial diversity of the measurements of the spatially located CR users [18]. Where CR users can cooperatively share their sensing information with neighbors for a combined decision making to introduce more accurate decisions than individual decisions [19]. Whereas, the presence of multiple sources helps to mitigate the effect of the multi-path at a single source which provides multiple independent realizations.…”

DISCERN: Enhanced Dynamic noISe varianCe based EneRgy sensing for cognitive radio using USRP at Wi‐Fi bands

“…The spectrum sensing is one of the critical functions in the cognitive cycle to detect unused spectrum bands in the radio environment. Prakash Borpatra Gohain et al 11 considered to improve conventional energy detection (CED) under noise uncertainty. The basic mass assignment (BMA) values minimize the noise variance when it knows exactly.…”