Effects of quantization and channel errors on sequential detection in cognitive radios

Abstract

This paper studies the impact of quantization and reporting channel errors on the performance of a sequential detection (SD) scheme for cooperative spectrum sensing in cognitive radios. The analyzed system model is a distributed parallel detection network in which the sensors quantize their local log-likelihood ratios (LLRs) and transmit them to the FC which makes the decision sequentially. The quantized local LLRs are transmitted through erroneous reporting channels. These reporting channels are modeled as binary symmetric channels (BSCs) that cause errors with a certain bit error probability (BEP). The quantization and reporting channel errors are shown to increase the average sample number (ASN) of the SD. Later the performances of the SD and fixed sample size (FSS) test are compared to show the superiority of the SD over the FSS test even in the presence of quantization and reporting channel errors regardless of the BEP. Even the ASN of the SD with I-bit quantization is shown to be smaller than the ASN of an unquantized FSS test with the same error probabilities in the considered scenario.

Latency Analysis for Sequential Detection in Low-Complexity Binary Radio Systems

“…and applying the finite difference approximation (116) in the Appendix together with the regularity constraint (34), gives…”

In a One-Bit Rush: Low-Latency Wireless Spectrum Monitoring With Binary Sensor Arrays

“…As the number of sufficient statistics for the multivariate Bernoulli distribution (23) scales O(2 M ), we base our SPRT analysis on a pessimistic replacement model, also residing within the exponential family [26]. This model holds a reduced set of sufficient statistics…”

“…with Φ being an elimination matrix canceling duplicate and constant diagonal statistics on zz T . The replacement with (38) is equivalent to the exact binary model (23) in the sense that it exhibits the same mean (28) and covariance (33) on the reduced set of statistics (38). Therefore, the achievable ASN with hard-limited multivariate Gaussian observations ( 21) can be calculated using (37) and (34), where…”

Cooperative Spectrum Sensing with Censoring of Cognitive Radios and MRC-Based Fusion in Fading and Shadowing Channels

“…Performance with a simple error correcting code yields a significant improvement (Choudhari, 2013). In Chaudhari (2012b), the authors evaluate the performance of sequential detection scheme for CSS in CRs with R-channel errors. The sequential local LLRs are transmitted through erroneous R-channels.…”

“…The R-channels are modeled as a simple binary symmetric channel (BSC) that induces errors with a certain bit error probability (BEP). However, in (Choudhari, 2012a, Choudhari, 2013, Chaudhari, 2012b CSS with distributed detection approach is mainly considered. In (Chen, 2014), the authors provide a tutorial on various cooperative techniques in cognitive networks, with emphasis on spectrum sensing and access based cooperation, interference constraint-based adaptive cooperative feedback, rate less network coding-based cooperative transmission.…”