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Wireless communication networks have evolved towards denser deployments with an increasingly large number of connected devices. Future generation networks including 5G and beyond are therefore expected to offer services at high data rate and ultra-low latency. To address this challenge, Multi-access Edge Computing (MEC) is a promising technology which can provide distributed and decentralized services in close proximity to mobile subscribers at low latency, and high rate access. In this project we work on a resource allocation problem for system level energy minimization in a network where multiple Access Points (APs) with integrated edge servers are equipped with massive MIMO antenna arrays. The MEC-APs simultaneously accommodate multiple co-channel users and provide computation offloading and wireless charging to ground users.
Relay-aided cooperative communication techniques represent a promising technology that improves performance in poor coverage areas by enabling ubiquitous coverage even for users in the most unfavorable channel conditions. In this project, we exploit stochastic geometry to study the potential of using user-assisted relaying in future cellular networks, propose geometric based cooperation policies, and study the effect of the additional transmission of the relaying nodes on interference and the performance of user-assisted relaying when deployed system-wide in a cellular network.
The current trend of increasing heterogeneity in communication networks brings a variety of communication needs and requirements, which often lead to different priorities. This is especially true in IoT applications which can generate messages with different degrees of importance. In this Project we introduce a priority-based coding scheme in the finite blocklength regime and apply the scheme to two different channels: the general discrete memoryless channel (DMC) and the AWGN channel. The scheme simultaneously encodes two messages, one with high and one with low priority, both requiring finite delay. The code structure allows the transmission of the high priority message with higher reliability and shorter decoding delay. We further derive tight and computationally efficient analytical upper bounds on the error probability in both the DMC and AWGN channel.
With the rapid evolution of wireless networks, energy efficiency is now deemed as a figure of merit for the design of next generation communication systems. We can envision future communication networks to employ relays capable of providing cooperation in terms of both information and energy. Far-field, radio frequency (RF) energy harvesting has recently garnered significant interest for communication systems with the prospect of simultaneous information and power transfer. In this work, we consider a MIMO communication system assisted by a full-duplex relay, where the relay is capable of harvesting energy. To focus on the benefits of MIMO and full duplex features, we consider the scenario in which the relay is self-sustained, that is, it has no power source of its own and hence relies solely on energy harvesting for its operations.
Fifth generation (5G) and beyond wireless systems aim to provide a minimum of 1 Gb/s data rate anywhere with up to 5 Gb/s for high mobility users and 50 Gb/s data rates for pedestrians by employing dense network of base stations and mobile users at mmWave spectrum. Even under beamforming, the high BS and user densities can drive cellular networks to be more interference rather than noise limited. While large adaptive arrays with narrow beams can boost the received signal power and hence reduce the impact of out-of-cell interference, this interference remains an important performance-limiting factor in dense mmWave networks. Modeling and characterization of wireless interference under these scenarios is essential for cellular system analysis and design.