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| Authors | Year | Title | Techniques and concept covered | Gaps or concept not covered |
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| G. Prieto et al. [10] | 2019 | Numerical analysis of histogram-based estimation techniques for entropy-based spectrum sensing | Entropy-based detection is proposed for spectrum sensing. Several rules for determining the number of bins in histogram are evaluated. Those rules are as follows: square root rule, Scott rule, and Sturges rule | This study focuses only on the Shannon entropy. It does not include other types of entropy such as Renyi, Kapur, and Tsallis entropy |
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| A. Fawzi et al. [3] | 2020 | Adaptive two-stage spectrum sensing model using energy detection and wavelet denoising for CR systems | Two-stage spectrum sensing techniques are proposed by combining two well methods: ED and WD | Even though it improves the performance of SS, the proposed technique is not robust to noise uncertainty at low SNR. Moreover, since WD is integrated with ED at low SNR, sensing time and computational complexity are very high |
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| A. D. Sahithi et al. [9] | 2020 | Analysis of energy detection spectrum sensing technique in cognitive radio | Cooperative spectrum sensing using ED is used to overcome the problem of uncertainty occurred due to fading and hidden primary terminal | This study does not focus on overcoming the problem of noise uncertainty |
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| F. Mashta et al. [17] | 2021 | An integrated parallel multistage spectrum sensing for cognitive radio | Two-stage and three-stage detector for SS are discussed in detail | Even though three-stage and two-stage spectrum sensing are performed, the overall performance of SS is not good at low SNR due to its sensitivity to noise uncertainty. Moreover, since the eigenvalue-based detector is used, the complexity of overall system increases |
| ED and maximum eigenvalue detector with different smoothing factors are used |
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