Enhancing the efficiency of cluster-based networks through MISO techniques

Towards the realization of the Internet of Things (IoT), cellular networks are expected to play a fundamental role, providing the ubiquitous coverage and global internetworking. However, due to the physical limitations, namely energy consumption or hardware complexity, of many of these objects, the direct communication with the cellular infrastructure is hindered. In this sense, cluster-based networks have been introduced as an efficient solution, offering coverage extension and energy savings. The energy efficiency and performance of these networks can be further enhanced if the devices can choose between two or more cluster-heads towards their connection to the infrastructure. In this paper, we propose a novel cluster-head (CH) selection algorithm, where the nodes can switch between different CHs, according to the corresponding signal strength, in order to maintain a predefined quality of service constraint. We show that the network reliability significantly increases, especially when considering mobile scenarios, where the connection to a CH may be not feasible, due to shadowing. In addition, the CHs are equipped with multiple antennas for enhanced performance. The performance of this scheme is theoretically investigated over correlated Nakagami-m multipath fading channels, subject also to shadowing. By considering Gamma distributed shadow effects, convenient expressions for important statistical metrics are obtained. The theoretical analysis is accompanied by representative performance evaluation results, complemented by equivalent computer simulated ones, which validate the accuracy of the proposed analysis.