Low Earth Orbit (LEO) nano-satellites can provide uplink connectivity for large numbers of distributed Internet of Things (IoT) sensing devices. To achieve a target Quality-of-Service (QoS), devices must send packets multiple times, due to collisions. This paper characterises the achievable set of terminal QoS targets, and determines the optimal uplink packet attempt rates. We show that QoS target feasibility is determined by the solution of a linear program (LP), and that the solution gives the optimal packet attempt rates. We show that the QoS targets can be modified using the shadow prices from the LP, to obtain feasibility. We show that our LP based approach can support greater than 30% more ground sensor terminals, compared to existing schemes.

This paper analyses the data message success rate for Internet of Things (IoT) sensing devices communicating over Low Earth Orbit (LEO) satellite links. We present an analytical framework for optimizing multi-objective multi-packet reception on the uplink. We present an analytical result for the probability of message success for a given ground terminal, and present an analytical result for the overall probability of message success, averaged across all terminals.

This paper considers millimeter-wave (mmWave) networks with hybrid beamforming communications, where base stations have a limited number of radio frequency (RF) chains. The base stations have overlapping coverage to overcome blockage issues in both downlink and uplink transmission. We propose a user association (UA) scheme that minimizes the time required for clearing data traffic of users in the coverage area. We formulate the UA problem as a time allocation problem, allocating time to user-base station links. We provide an innovative two-stage approach to solve this problem. Stage one optimizes a time fraction allocation for user-base station links. Then these time fractions are distributed across the RF chains at each base station using a fully distributed algorithm. Stage two then schedules the user-base station links, provably solving the UA minimum clearing time problem. We then characterize the achievability of any set of target user rates. Numerical results show that our proposed UA scheme achieves significantly reduced clearing times in comparison to baseline schemes.

This paper presents an efficient practical Zak-OTFS modulation implementation using time and frequency windowing methods. We present two general classes of delay-Doppler (DD) twisted convolution (TC) filters (Type-1 and Type-2), and show that they can be realized by time and frequency windowing functions. We then propose practical methods to generate time domain Zak-OTFS signals, for actual transmission, using the windowing functions. For Type-1, the signals are generated using an interpolation filter. For Type-2, they are generated using a form of precoded OFDM. We show that this allows a wide variety of pulse shapes to be implemented in practice for Zak-OTFS modulation. This was not previously possible. We also show that the Type-2 signals are more spectrally efficient than their Type-1 counterparts. Finally, we compare the channel predictability of the two implementations.

This paper provides capacity results for multi-user mm-wave hybrid-beamforming, and presents optimal joint beam allocation and user scheduling algorithms. We characterize the downlink capacity of a practical system with quantized analog beamforming code-books under the constraint that users cannot be scheduled at the same time if they are closer together than a beam width in angle. We show that the capacity region is determined by a small number of linear inequality constraints. We also present capacity-achieving scheduling algorithms that provide beam allocations guaranteeing that user rate requirements are met within each resource block. In particular, we propose “sand-filling” algorithms that are provably optimal and which have linear complexity. Intuitively, our schemes can be viewed in terms of filling containers with coloured sand, in such a way that the colours at any given height do not conflict with the colours in the other containers at the same height, where the containers represent the RF chains (i.e. the beamforming resources), and the coloured sand represents the users (and their rate requirements). We show a numerical example where the capacity of our scheme is 82% higher than a traditional resource partitioning scheme.

This paper presents a new distributed slot reservation frame-work for joint resource allocation and flow control in mmWave IAB networks. We derive the Dynamic Slot Reservation (DSR) algorithm from a novel approach to solve a minimum clearing time linear program in a completely distributed manner. The algorithm to solve this problem, the Static Slot Reservation (SSR) algorithm, is also a contribution of the paper. We compare the delay performance of the DSR algorithm with a well known optimal, centralized algorithm, the joint-MWM algorithm, for a realistic IAB network scenario of multi-hop flows. We show that flows that traverse several links have significantly lower delays under DSR than under the joint-MWM algorithm. This paper also provides an instantaneous rate control policy for IAB networks which changes flow rates based on the number of flows at each node in the network. The flow rates under this policy are the same as the steady-state flow rates achieved by the DSR algorithm. We prove that the proposed flow control policy provides stability for all flow arrival rate vectors that are achievable by any flow control policy. This paper provides distributed admission control policies to provide rate and/or latency guarantees to flows under dynamic scenarios with stochastic flow arrivals and changing access link rates.

We consider the stability region of a mmWave integrated access and backhaul (IAB) network with stochastic arrivals and time-varying link rates. In the scheduling of links, we consider a limit on the number of RF chains, and the half-duplex constraint which occurs due to the wireless backhaul links. We characterize the stability region, and propose a back-pressure policy for the IAB network under the RF chains and half-duplex constraints. To implement the back-pressure policy, it is required to compute the maximum weighted schedule, which is a complex problem in general. For the IAB network, we present a distributed message passing scheme to compute the maximum weighted schedule, with almost linear complexity. We also investigate a class of local scheduling policies for the IAB network, which have a smaller stability region in general, but require no message passing. We characterize the stability region for the local class, and show that it is same as the global stability region, if the link rates are un-varying. We provide a bound on the gap between local and global regions when the links are time varying. We propose a local max-weight algorithm which achieves the stability region for the local class, and we present numerical results.

In this article, we consider joint optimization of user association and resource allocation in three tier HetNets. We formulate the objective of minimizing the resources required to clear a given set of files, as a linear program. We show that the optimal user association is determined by a rate-biasing rule, where a bias value is associated with each BS. We show that each rate-bias value crucially only takes values from a finite set which we characterize. We present a complete analytical solution along with new structural results. Using these results, we present efficient distributed algorithms for optimal control of three tier HetNets. The method involves a 1D search for a resource variable at the macro-level, and 2D search at the pico-level for a resource variable and a bias value. We apply our results to a variety of hierarchical network examples.

We formulate a linear programming problem to find the minimum clearing time in HetNets. Although this program is NP hard in general, we consider particular topologies that arise in HetNets, including a two cell HetNet and a linear chain of HetNets, both with wireless backhaul, and we provide an efficient, greedy algorithm that provably solves the minimum clearing time problem for these networks. We show how this algorithm can be applied to jointly optimize the ABS time across multiple macros in a HetNet, and we demonstrate capacity gains of the algorithm, compared to standard approaches to Inter Cell Interference Coordination. This paper provides insight into how to manage interference in presence of more than one macro, and how to efficiently operate wireless backhaul in HetNets.