Low Complexity Node Selection Algorithms in MU-MIMO Energy Harvesting WSNs

The use of energy harvesting wireless sensor network (EH-WSN) is a rising wireless communication technology with a wide range of applications such as environment monitoring. Maximizing the number of samples collected by the sink from sensors is a key approach in order to minimize uncertainties for those applications. The considered system in this paper consists of an uplink scenario with EH sensors communicating with a non EH sink, equipped with multiple antennas, receiving data forwarded by the sensors. Using a zero-forcing (ZF) receiver, the data collector (i.e., sink) selects the largest possible set of transmitting sensor nodes to maximize the received quantity of information, while satisfying their signal-to-noise ratio quality of service (QoS) constraints. This paper presents efficient and simple EH node selection algorithms in EH-WSNs in order to maximize the number of selected sensors. The problem is formulated as an integer non linear program that can be optimally solved using an exhaustive search. Due to the prohibitive complexity of such a brute force approach, two low complexity and efficient heuristic algorithms are proposed to perform node selection decisions. Simulation results show the performance of the proposed algorithms and illustrate their adaptability and efficiency in the energy harvesting context.