Multimedia applications are characterized as delay-sensitive and high-bandwidth stipulating traffic sources. Supporting such demanding applications on cognitive radio sensor networks (CRSNs) with energy and spectrum constraints is a highly daunting task. In this paper, we propose a spectrum-aware cluster-based energy-efficient multimedia (SCEEM) routing protocol for CRSNs that jointly overcomes the formidable limitations of energy and spectrum. Clustering is exploited to support the quality of service (QoS) and energy-efficient routing by limiting the participating nodes in route establishment. In SCEEM routing, the number of clusters is optimally determined to minimize the distortion in multimedia quality that occurs due to packet losses and latency. Moreover, the cluster-head selection is based on the energy and relative spectrum awareness such that noncontiguous available spectrum bands are clustered and scheduled to provide continuous transmission opportunity. Routing employs clustering with hybrid medium access by combining carrier-sense multiple access (CSMA) and time-division multiple access (TDMA). TDMA operates for intracluster transmission, whereas CSMA is used for intercluster routing. Thus, a cross-layer design of routing, i.e., of medium access control (MAC) and physical layers, provides efficient multimedia routing in CRSNs, which is revealed through simulation experiments.

Multi-stream carrier aggregation (MSCA) has been recently proposed as a mechanism to increase the amount of bandwidth available to users for heterogeneous networks (HetNets) in 5G wireless systems. Previous studies have focused only on maximizing the network capacity and fairness, without considering the energy efficiency of the MSCA. In this paper, the use of MSCA to minimize the energy consumption in a multi-layer HetNet is studied. The convexity of the energy minimization problem is examined, leading to the need of a quasi-convex relaxation. With this approximation, an algorithm bisection method for energy minimization is designed to solve the energy minimization problem and obtains an optimum cell-association policy. Since the operators are generally interested in a balance between the energy minimization and capacity maximization, such multi-objective optimization is needed, and we studied it in this paper. The two aforementioned conflicting objectives can be jointly analyzed and solved through scalarization, even though the energy minimization has a quasi-convex objective function, and not a convex one. Performance evaluation is provided to identify the achievable energy savings of our proposed algorithm and to characterize the tradeoffs between the energy minimization and capacity maximization in a multi-layer HetNet in 5G systems that support MSCA.