High-fidelity, real-time interactive applications are envisioned with the emergence of the Internet of Things (IoT) and tactile Internet by means of ultra-reliable low-latency communications (URLLC). Exploiting time diversity for fulfilling the URLLC requirements in an energy efficient manner is a challenging task due to the nontrivial interplay among packet size, retransmission rounds and delay, and transmit power. In this paper, we study the fundamental energy-latency tradeoff in URLLC systems employing incremental redundancy (IR) hybrid automatic repeat request (HARQ). We cast the average energy minimization problem with a finite blocklength (latency) constraint and feedback delay, which is non-convex. We propose a dynamic programming algorithm for energy efficient IR-HARQ optimization in terms of number of retransmissions, blocklength and power per round. Numerical results show that our IR-HARQ approach could provide around 25% energy saving compared to one-shot transmission (no HARQ).

This article introduces a novel family of decentralised caching policies, applicable to wireless networks with finite storage at the edge-nodes (stations). These policies are based on the Least-Recently-Used replacement principle, and are, here, referred to as spatial multi-LRU. Based on these, cache inventories are updated in a way that provides content diversity to users who are covered by, and thus have access to, more than one station. Two variations are proposed, namely the multi-LRU-One and -All, which differ in the number of replicas inserted in the involved caches. By introducing spatial approximations, we propose a Che-like method to predict the hit probability, which gives very accurate results under the Independent Reference Model (IRM). It is shown that the performance of multi-LRU increases the more the multicoverage areas increase, and it approaches the performance of other proposed centralised policies, when multi-coverage is sufficient. For IRM traffic multi-LRU-One outperforms multi-LRU-All, whereas when the traffic exhibits temporal locality the -All variation can perform better.

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Quality of service (QoS) provisioning in nextgeneration mobile communications systems entails a deep understanding of the delay performance. The delay in wireless networks is strongly affected by the traffic arrival process and the service process, which in turn depends on the medium access protocol and the signal-to-interference-plus-noise ratio (SINR) distribution. In this work, we characterize the conditional distribution of the service process given the point process in Poisson bipolar networks. We then provide an upper bound on the delay violation probability combining tools from stochastic network calculus and stochastic geometry. Furthermore, we analyze the delay performance under statistical queueing constraints using the effective capacity formulation. The impact of QoS requirements, network geometry and link distance on the delay performance is identified. Our results provide useful insights for guaranteeing stringent delay requirements in large wireless networks.

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