Time slotted channel hopping (TSCH) is a mediumaccess control (MAC) protocol introduced in IEEE802.15.4e standard, addressing low-power requirements of the Internet of Things and low-power and lossy networks. The 6TiSCH operation (6top) sublayer of IEEE802.15.4e defines the schedule that includes sleep, transmit, and receive routines of the nodes. However, the standard does not specify the design of the schedule. In this article, we propose a contention-based proportional fairness transmission scheme for TSCH networks to maximize the system throughput addressing the fair allocation of resources to the nodes. We propose a convex programming-based method to achieve the fairness and throughput objectives. We model TSCH MAC as a multichannel slotted ALOHA and analyze it for a schedule given by the 6top layer. Performance metrics, such as throughput, delay, and energy spent per successful transmission, are derived and validated through simulations and real-time testbed implementations.

High demand for reliability, low latency, seamless connectivity lead to the 5G era. 5G cellular networks employ a random access based preamble transmission procedure for the initial locking of User Equipment (UEs) to a base station (gNB) and uplink resource scheduling. It is of utmost importance that we evaluate the factors that aid and those that limit the random access procedure in achieving its envisaged goal. In this paper, we develop an analytical model for random access procedure for connection establishment in 5G when beamforming is employed. The random access medium is modelled as a multi-channel slotted Aloha system. We use an equilibrium point analysis framework to derive the performance metrics namely, the rate at which UEs can lock on to a gNB and the average and variance of the time taken by a new UE to establish connection with the base station. We analyse the impact of the retransmission limit and the number of available preambles for random access on the performance of connection establishment of a UE. Our analysis brings out the importance of the choice of base station configurations with respect to the user demographics of a 5G NR cell.

Time Slotted Channel Hopping (TSCH) behavioural mode has been introduced in IEEE 802.15.4e standard to address the ultra-high reliability and ultra-low power communication requirements of Industrial Internet of Things (IIoT) networks. Scheduling the packet transmissions in IIoT networks is a difficult task owing to the limited resources and dynamic topology. In this paper, we propose a phasic policy gradient (PPG) based TSCH schedule learning algorithm. The proposed PPG based scheduling algorithm overcomes the drawbacks of totally distributed and totally centralized deep reinforcement learning-based scheduling algorithms by employing the actor-critic policy gradient method that learns the scheduling algorithm in two phases, namely policy phase and auxiliary phase.

IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) standard has gained prominence in the Industrial Internet of Things (IIoT) research community due to its potency in improving reliability, providing low latency and low power consumption. In TSCH, a schedule orchestrates the communication in the networks between the nodes. The design and maintenance of the schedule are out of the standard's scope, and is open for implementation. In this paper, we address the design problem of an optimal scheduling algorithm in TSCH networks. We design a TSCH schedule inspired by a biogeographical aspect of bird flocking. Like bird flocks, which migrate to find a suitable habitat depending on several features like seasons, food availability, etc., a TSCH network can also end up in an optimal schedule for its dynamic requirements. With this motivation, we design a biogeography inspired optimal schedule (BIOS) for TSCH networks incorporating the features such as migration and mutation to learn the best schedule. We show that the proposed BIOS-TSCH schedule is also suited for the sporadic and dynamic networks. We evaluate the performance of BIOS-TSCH in terms of convergence, delay and radio duty cycle. We show that the proposed BIOS-TSCH schedule achieves an improvement of 60% in delay performance and up to 40% in energy efficiency compared to the minimal scheduling function.