Capacity Region and Degrees of Freedom of Bidirectional Networks

The increasing complexity of communication networks in size and density provides us enormous opportunities to exploit interaction among multiple nodes, thus enabling higher rate of data streams. On the flip side, however, this complexity comes with challenges in managing interference that multiple source-destination pairs in the network may cause to each other. In this dissertation, we make progress on how to exploit the opportunities, as well as how to overcome the challenges for various communication networks. In the first part, we focus on developing fundamental principles for communication network design, especially networks with multiple antenna transceivers, with an emphasis on (1) understanding the role of feedback and cooperation, and (2) developing interference management methods. In this part, we find that feedback and cooperation have promising roles in improving the capacity performance of several interference networks. We show that in stark contrast to the point-to-point case, a limited feedback can improve the capacity of interference-limited networks. In fact, the improvement can be unbounded. This result shows that feedback can have a potentially significant role to play in mitigating interference. Then, in part two we study several bidirectional networks. We study the bidirectional diamond network and show that for deterministic and some Gaussian models the capacity is doubled for full-duplex channel in comparison with one-way networks. In addition, we study the degrees of freedom of two-way four-unicast MIMO networks, and provide upper and lower bounds that are tight in several cases. We also study the impact of caching in relay nodes for these models. We find a number of cases that bidirectional links can double the degrees of freedom with the help of relay caching and/or multiple relay antennas

Advanced Technologies for Device-to-device Communications Underlaying Cellular Networks

The past few years have seen a major change in cellular networks, as explosive growth in data demands requires more and more network capacity and backhaul capability. New wireless technologies have been proposed to tackle these challenges. One of the emerging technologies is device-to-device (D2D) communications. It enables two cellular user equip- ment (UEs) in proximity to communicate with each other directly reusing cellular radio resources. In this case, D2D is able to of oad data traf c from central base stations (BSs) and signi cantly improve the spectrum ef ciency of a cellular network, and thus is one of the key technologies for the next generation cellular systems. Radio resource management (RRM) for D2D communications and how to effectively exploit the potential bene ts of D2D are two paramount challenges to D2D communications underlaying cellular networks. In this thesis, we focus on four problems related to these two challenges. In Chapter 2, we utilise the mixed integer non-linear programming (MINLP) to model and solve the RRM optimisation problems for D2D communications. Firstly we consider the RRM optimisation problem for D2D communications underlaying the single carrier frequency division multiple access (SC-FDMA) system and devise a heuristic sub- optimal solution to it. Then we propose an optimised RRM mechanism for multi-hop D2D communications with network coding (NC). NC has been proven as an ef cient technique to improve the throughput of ad-hoc networks and thus we apply it to multi-hop D2D communications. We devise an optimal solution to the RRM optimisation problem for multi-hop D2D communications with NC. In Chapter 3, we investigate how the location of the D2D transmitter in a cell may affect the RRM mechanism and the performance of D2D communications. We propose two optimised location-based RRM mechanisms for D2D, which maximise the throughput and the energy ef ciency of D2D, respectively. We show that, by considering the location information of the D2D transmitter, the MINLP problem of RRM for D2D communications can be transformed into a convex optimisation problem, which can be ef ciently solved by the method of Lagrangian multipliers. In Chapter 4, we propose a D2D-based P2P le sharing system, which is called Iunius. The Iunius system features: 1) a wireless P2P protocol based on Bittorrent protocol in the application layer; 2) a simple centralised routing mechanism for multi-hop D2D communications; 3) an interference cancellation technique for conventional cellular (CC) uplink communications; and 4) a radio resource management scheme to mitigate the interference between CC and D2D communications that share the cellular uplink radio resources while maximising the throughput of D2D communications. We show that with the properly designed application layer protocol and the optimised RRM for D2D communications, Iunius can signi cantly improve the quality of experience (QoE) of users and of oad local traf c from the base station. In Chapter 5, we combine LTE-unlicensed with D2D communications. We utilise LTE-unlicensed to enable the operation of D2D in unlicensed bands. We show that not only can this improve the throughput of D2D communications, but also allow D2D to work in the cell central area, which normally regarded as a “forbidden area” for D2D in existing works. We achieve these results mainly through numerical optimisation and simulations. We utilise a wide range of numerical optimisation theories in our works. Instead of utilising the general numerical optimisation algorithms to solve the optimisation problems, we modify them to be suitable for the speci c problems, thereby reducing the computational complexity. Finally, we evaluate our proposed algorithms and systems through sophisticated numer- ical simulations. We have developed a complete system-level simulation framework for D2D communications and we open-source it in Github: https://github.com/mathwuyue/py- wireless-sys-sim

Interference management with mismatched partial channel state information

We study the fundamental limits of communications over multi-layer wireless networks where each node has only limited knowledge of the channel state information. In particular, we consider the scenario in which each source-destination pair has only enough information to perform optimally when other pairs do not interfere. Beyond that, the only other information available at each node is the global network connectivity. We propose a transmission strategy that solely relies on the available limited knowledge and combines coding with interference avoidance. We show that our proposed strategy goes well beyond the performance of interference avoidance techniques. We present an algebraic framework for the proposed transmission strategy based on which we provide a guarantee of the achievable rate. For several network topologies, we prove the optimality of our proposed strategy by providing information-theoretic outer-bounds

Coverage Optimization with a Dynamic Network of Drone Relays

The integration of aerial base stations carried by drones in cellular networks offers promising opportunities to enhance the connectivity enjoyed by ground users. In this paper, we propose an optimization framework for the 3-D placement and repositioning of a fleet of drones with a realistic inter-drone interference model and drone connectivity constraints. We show how to maximize network coverage by means of an extremal-optimization algorithm. The design of our algorithm is based on a mixed-integer non-convex program formulation for a coverage problem that is NP-Complete, as we prove in the paper. We not only optimize drone positions in a 3-D space in polynomial time, but also assign flight routes solving an assignment problem and using a strong geometrical tool, namely Bézier curves, which are extremely useful for non-uniform and realistic topologies. Specifically, we propose to fly drones following Bézier curves to seek the chance of approaching to clusters of ground users. This enhances coverage over time while users and drones move. We assess the performance of our proposal for synthetic scenarios as well as realistic maps extracted from the topology of a capital city. We demonstrate that our framework is near-optimal and using Bézier curves increases coverage up to 47 percent while drones move

Recent Advances in Cellular D2D Communications

Device-to-device (D2D) communications have attracted a great deal of attention from researchers in recent years. It is a promising technique for offloading local traffic from cellular base stations by allowing local devices, in physical proximity, to communicate directly with each other. Furthermore, through relaying, D2D is also a promising approach to enhancing service coverage at cell edges or in black spots. However, there are many challenges to realizing the full benefits of D2D. For one, minimizing the interference between legacy cellular and D2D users operating in underlay mode is still an active research issue. With the 5th generation (5G) communication systems expected to be the main data carrier for the Internet-of-Things (IoT) paradigm, the potential role of D2D and its scalability to support massive IoT devices and their machine-centric (as opposed to human-centric) communications need to be investigated. New challenges have also arisen from new enabling technologies for D2D communications, such as non-orthogonal multiple access (NOMA) and blockchain technologies, which call for new solutions to be proposed. This edited book presents a collection of ten chapters, including one review and nine original research works on addressing many of the aforementioned challenges and beyond

Interference management for moving networks in ultra-dense urban scenarios

The number of users relying on broadband wireless connectivity while riding public transportation vehicles is increasing significantly. One of the promising solutions is to deploy moving base stations on public transportation vehicles to form moving networks (MNs) that serve these vehicular users inside the vehicles. In this study, we investigated the benefits and challenges in deploying MNs in ultra-dense urban scenarios. We identified that the key challenge limiting the performance of MNs in ultra-dense urban scenarios is inter-cell interference, which is exacerbated by the urban canyon effects. To address this challenge, we evaluated different inter-cell interference coordination and multi-antenna interference suppression techniques for MNs. We showed that in using MNs together with effective interference management approaches, the quality of service for users in vehicles can be significantly improved, with negligible impacts on the performance of regular outdoor users