Cognitive radio (CR) is a device which can detect wireless communication channels that are not in use and adapt its parameters intelligently. Networks with CRs use the available frequency bands much more efficiently and hence have higher data rates compare to traditional radios. Spectrum sensing is the class of techniques used by CRs to understand its wireless environment. Recent research on evaluating multi-band spectrum sensing algorithms is limited to only algorithm complexity and optimization; therefore, the primary goal of the study is to devise a novel framework that analyzes a multi-band spectrum sensing algorithm in terms of energy consumption and algorithm efficiency. The proposed structure leads to a comparison and evaluation of a large class of multi-band spectrum sensing algorithms. Multi-band spectrum sensing search methods such as linear, random and binary are evaluated for energy loss and detection performance using the proposed framework