Interference-Aware Downlink and Uplink Resource Allocation in HetNets with D2D Support

We address the resource allocation problem in an LTE-based 2-tier heterogeneous network where in-band D2D communications are supported under network control. The different communication paradigms share the same radio resources, thus they may interfere. We devise a dynamic programming approach to efficiently schedule download and upload traffic, by 1) efficiently matching communicating endpoints and 2) assigning radio resources in an interference-aware manner while accounting for the characteristics of the content to be delivered. To this end, we develop an accurate model of the system and apply approximate dynamic programming to solve it. Our solution allows us to deal with realistic large-scale scenarios. In such scenarios, we compare our approach to today's networks where eICIC techniques and proportional fairness scheduling are implemented. Results highlight that our solution increases the system throughput while greatly reducing energy consumption. We also show that D2D mode, established either in the downlink or uplink, can effectively support delivery of highly popular content without significantly harming macrocell or microcell traffic, leading to increased system capacity. Interestingly, we find that D2D mode can also be a low-cost alternative to microcells

Resource and power management in next generation networks

The limits of today’s cellular communication systems are constantly being tested by the exponential increase in mobile data traffic, a trend which is poised to continue well into the next decade. Densification of cellular networks, by overlaying smaller cells, i.e., micro, pico and femtocells, over the traditional macrocell, is seen as an inevitable step in enabling future networks to support the expected increases in data rate demand. Next generation networks will most certainly be more heterogeneous as services will be offered via various types of points of access (PoAs). Indeed, besides the traditional macro base station, it is expected that users will also be able to access the network through a wide range of other PoAs: WiFi access points, remote radio-heads (RRHs), small cell (i.e., micro, pico and femto) base stations or even other users, when device-to-device (D2D) communications are supported, creating thus a multi-tiered network architecture. This approach is expected to enhance the capacity of current cellular networks, while patching up potential coverage gaps. However, since available radio resources will be fully shared, the inter-cell interference as well as the interference between the different tiers will pose a significant challenge. To avoid severe degradation of network performance, properly managing the interference is essential. In particular, techniques that mitigate interference such Inter Cell Interference Coordination (ICIC) and enhanced ICIC (eICIC) have been proposed in the literature to address the issue. In this thesis, we argue that interference may be also addressed during radio resource scheduling tasks, by enabling the network to make interference-aware resource allocation decisions. Carrier aggregation technology, which allows the simultaneous use of several component carriers, on the other hand, targets the lack of sufficiently large portions of frequency spectrum; a problem that severely limits the capacity of wireless networks. The aggregated carriers may, in general, belong to different frequency bands, and have different bandwidths, thus they also may have very different signal propagation characteristics. Integration of carrier aggregation in the network introduces additional tasks and further complicates interference management, but also opens up a range of possibilities for improving spectrum efficiency in addition to enhancing capacity, which we aim to exploit. In this thesis, we first look at the resource allocation in problem in dense multitiered networks with support for advanced features such as carrier aggregation and device-to-device communications. For two-tiered networks with D2D support, we propose a centralised, near optimal algorithm, based on dynamic programming principles, that allows a central scheduler to make interference and traffic-aware scheduling decisions, while taking into consideration the short-lived nature of D2D links. As the complexity of the central scheduler increases exponentially with the number of component carriers, we further propose a distributed heuristic algorithm to tackle the resource allocation problem in carrier aggregation enabled dense networks. We show that the solutions we propose perform significantly better than standard solutions adopted in cellular networks such as eICIC coupled with Proportional Fair scheduling, in several key metrics such as user throughput, timely delivery of content and spectrum and energy efficiency, while ensuring fairness for backward compatible devices. Next, we investigate the potentiality to enhance network performance by enabling the different nodes of the network to reduce and dynamically adjust the transmit power of the different carriers to mitigate interference. Considering that the different carriers may have different coverage areas, we propose to leverage this diversity, to obtain high-performing network configurations. Thus, we model the problem of carrier downlink transmit power setting, as a competitive game between teams of PoAs, which enables us to derive distributed dynamic power setting algorithms. Using these algorithms we reach stable configurations in the network, known as Nash equilibria, which we show perform significantly better than fixed power strategies coupled with eICIC

Interference-Aware Downlink and Uplink Resource Allocation in HetNets With D2D Support

We address the resource allocation problem in an LTE-based 2-tier heterogeneous network where in-band D2D communications are supported under network control. The different communication paradigms share the same radio resources, thus they may interfere. We devise a dynamic programming approach to efficiently schedule download and upload traffic, by 1) efficiently matching communicating endpoints and 2) assigning radio resources in an interference-aware manner while accounting for the characteristics of the content to be delivered. To this end, we develop an accurate model of the system and apply approximate dynamic programming to solve it. Our solution allows us to deal with realistic large-scale scenarios. In such scenarios, we compare our approach to today's networks where eICIC techniques and proportional fairness scheduling are implemented. Results highlight that our solution increases the system throughput while greatly reducing energy consumption. We also show that D2D mode, established either in the downlink or uplink, can effectively support delivery of highly popular content without significantly harming macrocell or microcell traffic, leading to increased system capacity. Interestingly, we find that D2D mode can also be a low-cost alternative to microcell

The Coexistence of D2D Communication under Heterogeneous Cellular Networks (HetNets)

Device-to-Device (D2D) communication is a promising technique for supporting the stringent requirements of the fifth-generation cellular network (5G). This new technique has garnered significant attention in cellular network standards for proximity communication as a means to improve cellular spectrum utilization, to decrease user equipment energy consumption, and to reduce end-to-end delay. This dissertation reports an investigation of D2D communication coexistence under 5G heterogeneous cellular network (HetNets) in terms of spectrum allocation and energy efficiency. The work reported herein describes a low-complexity D2D resource allocation algorithm for downlink (DL) resource reuse that can be leveraged to improve network throughput. Notably, cross-tier interference was considered when establishing D2D communication (e.g., macro base station to D2D links; small base station to D2D links; and D2D communication to cellular links served by the macro and small base stations). An allocation algorithm was introduced to reduce interference from D2D to cellular when a single D2D link is sharing cellular resources. Performance of the proposed algorithm was evaluated and compared to various resource allocations. Simulation results demonstrated that the proposed algorithm improves overall system throughput. This allocation algorithm achieved a near-optimal solution when compared with a brute force approach. This dissertation also presents a novel framework for optimizing the energy efficiency of D2D communication coexistence with HetNets in DL transmission. This optimization problem was mathematically formulated in terms of mode selection, power control, and resources allocation (i.e., NP-hard problem). The optimization fraction problem was simplified based on network load and was solved using various optimization methods. An innovative dynamic mode selection based on Fuzzy clustering was also introduced. Proposed scheme performance was evaluated and compared to the standard algorithm. Simulation validated the advantage of the proposed framework in terms of performance gain in both energy efficiency and the number of successfully connected D2D users. Moreover, the energy efficiency of HetNets with D2D compatibility was improved. Finally, this dissertation details a stochastic analytical model for an LTE scheduler with D2D communication. By assuming exponential distributions for users scheduling time, a throughput estimation model was developed using two-dimensional Continuous Time Markov chains (2D-CTMC) of birth-death type. The proposed model will predict the expected number of D2D operated in dedicated and reuse mode, as well as the systems long-term throughput