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In this paper, we propose a utility-based spectrum aggregation algorithm to enhance the performance of a cognitive radio network considering multiple objectives: (i) maximization of overall throughput, (ii) reduction of channel switching, (iii) reducing the number of sub-channels comprising the aggregate channel, aimed at opportunistic spectrum use by secondary users (SUs). These three objectives are integrated into a weighted sum utility function. The weight associated with each objective can be set differently (typically done manually) depending on the metric to be optimized. In this article however, we propose and evaluate an automatic mechanism for setting weights. The proposed algorithm including the learning module allows for automated (no manual intervention) adaptable setting of objective- function weights depending on the environment changes and its performance is also shown via the simulation …