A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges

Abstract

Cognitive radio (CR), as a concept based on the ability to detect and share the unutilised spectrum, has been envisioned as a promising candidate to improve the efficiency of frequency spectrum assignments. For the realisation of the CR concept, energy detection (ED), as one of the available spectrum sensing methods, is broadly considered because of its low computational complexity and implementation costs. Due to the vast usage of the orthogonal frequency division multiplexing (OFDM) technique in contemporary communication systems, the ED of OFDM signals in the CR networks has become important for practical realisation. Since the ED accuracy of the OFDM signals can be improved by the sensing threshold adaptation, this paper surveys the impact of noise variations and dynamic threshold (DT) adaptation on the ED performance of OFDM signals. Analyses were performed by the simulation of the ED related to OFDM signals transmitted in the margin or rate adaptive and combined margin and rate adaptive OFDM systems. The results obtained through extensive simulations provide fundamental insights into how different factors, including the transmission power, the signal to noise ratio, the false alarm probability and the sample quantity, affect the ED efficiency. Comprehensive analyses of the obtained results indicate the main ED weaknesses and how the appropriate selection of analysed factors can enhance the ED processes for different OFDM systems. The observed ED weaknesses were further thoroughly surveyed, and the open issues and challenges related to the enhancement of the main ED limitations have been elaborated. The presented survey results can serve as a basis for the improvement of a broadly accepted ED method in CR networks.

Algorithm for Evaluating Energy Detection Spectrum Sensing Performance of Cognitive Radio MIMO-OFDM Systems

“…Additionally, the impact of different Tx powers (100 mW, 1 W and 10 W) in SISO and both symmetric (2 × 2) and asymmetric (2 × 4, 2 × 6) MIMO systems in relation to detection probability has been presented in Figure 4 for SNR levels of −20 dB. The results presented for SISO systems in Figure 3 a and Figure 4 a have been similar to those obtained in [ 21 ]. As shown in Figure 3 and Figure 4 , a higher detection probability will be accomplished in both SISO and MIMO systems when the PU signal is transmitted at a higher Tx power.…”

“…The simulation results show that NU has a significant and negative influence on ED performance. In [ 21 ], we further show that DT adaptation positively impacts the ED process. The results presented in [ 21 ] confirm an improvement in the ED performance in terms of the better detection probabilities for the lower SNR levels, the number of samples used in the detection process and the PU Tx powers, when compared to the ED lacking a DT adaptation.…”

“…However, this complexity is still significantly lower than the implementation complexity of some of the other local spectrum-sensing methods requesting exact knowledge of CSI. According to the already presented research in this area for other prominent local SS methods, such as matched filter, waveform-based and cyclostationary feature detection, the computation complexity of those methods are shown to be higher than the complexity of the ED method [ 21 ]. This is a consequence of a higher amount of prior PU information needed for successful SS.…”

“…Although previous research presented in [ 10 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 ] considers the ED process in MIMO transmission systems, an algorithm that enables the simulation analysis of the ED performance in MIMO-OFDM systems based on the SLC method is still missing. According to our knowledge, this is the first paper that deals with an algorithm which enables such analyses through ROC curves developed for the different operating parameters of the analyzed MIMO-OFDM systems.…”

“…The ED model for SISO systems has been presented in [ 21 , 31 ]. The ED model based on SLC for MISO systems is developed in [ 22 , 32 ].…”