Multibeam antenna arrays (MBAAs) have the capability to improve the capacity of a wireless network by facilitating simultaneous transmissions to multiple users. However, in practical deployments of wireless personal or local area networks (WPANs/WLANs) where piconet coordinators or access points (PNCs/APs) are deployed with MBAAs, it is quite likely to observe non-uniform node densities in various regions. To optimally utilize MBAAs in such scenarios, concurrent transmission scheduling in WPANs/WLANs is formulated as a multi-objective optimization problem. Then, a practical heuristic transmission scheduler that aims to maximize the number of concurrent communications by dynamically configuring the directions of beams is proposed. In addition, a service tag based fair scheduler is also proposed to achieve weighted fairness in WPANs/WLANs with MBAAs. Our results show that the performance improvements provided by the proposed heuristic scheduler are higher for antennas with lower beamwidths, and as the non-uniformity in the network increases, the traffic supported in the network increases in the range 24-41%, compared to the existing methods. The proposed service tag based scheduler can further improve the network throughput and achieve better fairness at the cost of a few beam direction reconfigurations, as compared to the existing methods and our heuristic scheduler.

Millimeter Wave (mmWave) communications are evolving as a potential and promising technology to address the ever increasing mobile data rate requirements. This paper addresses fair scheduling in directional antenna based mmWave wireless personal and local area networks with non-uniform traffic demand. Due to their small wavelength, mmWave signals are susceptible to blockage. The proposed fair schedulers handle the link blockage problem through relaying, and are capable of providing end-to-end fair bandwidth allocation to relay flows. To achieve differentiated and fair service allocation to various regions of the network while using only limited flow related information, a service tag based scheduler is proposed in this paper. Then, the performance bounds on the minimum throughput and unfairness of this scheduler are obtained. To approximate the performance of the service tag based scheduler while minimizing the control overhead, a heuristic fair scheduler is also proposed. Results from extensive simulations conducted in a mmWave WPAN deployed to support high data rate applications show the performance advantages of the proposed schedulers, compared to existing fair schedulers, in terms of throughput and fairness.

The IEEE 802.11ah standard has been developed to provide Internet access to a large number of devices in the Internet of Things (IoT) and machine-to-machine (M2M) networks. To handle contention from a large number of devices and reduce the collision probability, IEEE 802.11ah partitions nodes into groups by adopting a group- based MAC protocol. The formed groups may consist of nodes with different traffic patterns and hence, the data rate requirements of nodes in a group (and consequently the groups themselves) may not be uniform. To maximize the throughput while minimizing unfairness across groups, this paper formulates fair scheduling in IEEE 802.11ah networks as a multi-objective optimization problem. To maintain fairness among the nodes in a group, contention window size selection of nodes is formulated as an integer programming problem. Since it is difficult to solve these problems in real time, heuristic methods are also proposed. Performance of the proposed methods is evaluated in a dense IoT network and compared with the existing methods. As the number of nodes and groups increase, the proposed method consistently shows a superior performance in terms of fairness, throughput, delay, and power consumption, compared to the existing methods.

The IEEE 802.11ah standard can provide cost-effective Internet access to a large number of devices in newly evolving Internet-of-Things (IoT) and machine-to-machine (M2M) networks. To handle high collision probability caused by a large number of devices, it adopts a group-based protocol at the MAC layer and divides nodes (or sensors) into a number of groups. The formed groups may not be uniform in terms of data rate requirements, since each group is a combination of sensors with different traffic characteristics. To achieve fair resource utilization across the groups which in turn maximizes the channel utilization, this paper formulates fair grouping in IEEE 802.11ah networks as an optimization problem, and we develop a heuristic method to solve the problem in real-time. In addition, to ensure fair channel utilization by the nodes in each group, a contention window selection and adjustment method is proposed. Results from extensive simulations conducted in a dense IoT network show that the proposed fairness model achieves a superior performance than the existing methods in terms of throughput, packet delay, energy efficiency, and fairness.

With their capability to support high data rates, millimeter-Wave (mmWave) communications are evolving as a promising and potential technology to support high data rate applications in short range networks. This paper addresses the problem of fair scheduling in mmWave wireless personal and local area networks (WPANs/WLANs) to support applications with varying quality of service (QoS) requirements. To ensure fairness while exploiting the spatial reuse facilitated by directional antennas, concurrent transmission scheduling in mmWave WPANs/WLANs is formulated as a multi-objective optimization problem. Two heuristic schedulers are developed to obtain a schedule in real-time. These schedulers first satisfy the minimum QoS requirements of as many flows as possible, and then, allocate the remaining bandwidth to various flows while ensuring long-term and short-term fairness among the flows. Results from extensive simulations conducted in a dense mmWave WPAN show that the proposed fair schedulers provide better fairness and throughput, compared to existing methods.

Directional antennas provide many advantages such as higher gain, increased capacity, longer range, and reduced interference by concentrating radio signal energy in one direction. This paper addresses concurrent transmission scheduling in wireless personal or local area networks deployed with directional antennas. In typical network deployment scenarios, it is quite likely to have non-uniform node densities and traffic demands in various parts of the network. In such situations, to provide load-based service to various parts of the network while aiming to maximize the spatial reuse, this paper proposes a zone-based concurrent data transmission scheduling method. Simulation results show that the proposed method can support a larger number of flows while satisfying a greater fraction of the traffic demands from highly loaded regions, compared to existing methods.