Optimizing Information Freshness in a Multiple Access Channel with Heterogeneous Devices

In this work, we study age-optimal scheduling with stability constraints in a multiple access channel with two heterogeneous source nodes transmitting to a common destination. The first node is connected to a power grid and it has randomly arriving data packets. Another energy harvesting (EH) sensor monitors a stochastic process and sends status updates to the destination. We formulate an optimization problem that aims at minimizing the average age of information (AoI) of the EH node subject to the queue stability condition of the grid-connected node. First, we consider a Probabilistic Random Access (PRA) policy where both nodes make independent transmission decisions based on some fixed probability distributions. We show that with this policy, the average AoI is equal to the average peak AoI, if the EH node only sends freshly generated samples. In addition, we derive the optimal solution in closed form, which reveals some interesting properties of the considered system. Furthermore, we consider a Drift-Plus-Penalty (DPP) policy and develop AoI-optimal and peak-AoI-optimal scheduling algorithms using the Lyapunov optimization theory. Simulation results show that the DPP policy outperforms the PRA policy in various scenarios, especially when the destination node has low multi-packet reception capabilities.Comment: 13 pages, 8 figures, accepted for publication in IEEE Open Journal of the Communications Societ

User association for energy harvesting relay stations in cellular networks

We consider a cellular wireless network enhanced by relay stations that are powered by renewable energy sources. Such a network consists of the macro base stations (BS), relay stations (RSs), and many mobile stations (MSs). In addition to the traditional data/voice transmission between the BS and the MSs, a higher service tier may be provided by using the energy harvesting RSs for some MSs. We propose a network scenario utilizing the energy harvesting relay stations to improve the service quality without taking the additional licensed frequency band and transmission power, and design a user association algorithm for the energy harvesting RSs in such a network. The goal is to assign each MS an RS for relaying its signal to minimize the probability of the relay service outage, i.e, the probability that an MS’s relay service request is rejected. First, we propose a network scenario and develop a mathematical model to estimate the rejection probability for a given user association. We then propose a low-complexity local search algorithm, which balances the computational complexity and the performance, to obtain a locally optimal user association. Simulation results are provided to demonstrate the superior performance of the proposed techniques over the traditional methods

Design, analysis and optimization of visible light communications based indoor access systems for mobile and internet of things applications

Demands for indoor broadband wireless access services are expected to outstrip the spectrum capacity in the near-term spectrum crunch . Deploying additional femtocells to address spectrum crunch is cost-inefficient due to the backhaul challenge and the exorbitant system maintenance. According to an Alcatel-Lucent report, most mobile Internet access traffic happens indoors. To alleviate the spectrum crunch and the backhaul challenge problems, visible light communication (VLC) emerges as an attractive candidate for indoor wireless access in the 5G architecture. In particular, VLC utilizes LED or fluorescent lamps to send out imperceptible flickering light that can be captured by a smart phone camera or photodetector. Leveraging power line communication and the available indoor infrastructure, VLC can be utilized with a small one-time cost. VLC also facilitates the great advantage of being able to jointly perform illumination and communications. Integration of VLC into the existing indoor wireless access networks embraces many challenges, such as lack of uplink infrastructure, excessive delay caused by blockage in heterogeneous networks, and overhead of power consumption. In addition, applying VLC to Internet-of-Things (IoT) applications, such as communication and localization, faces the challenges including ultra-low power requirement, limited modulation bandwidth, and heavy computation and sensing at the device end. In this dissertation, to overcome the challenges of VLC, a VLC enhanced WiFi system is designed by incorporating VLC downlink and WiFi uplink to connect mobile devices to the Internet. To further enhance robustness and throughput, WiFi and VLC are aggregated in parallel by leveraging the bonding technique in Linux operating system. Based on dynamic resource allocation, the delay performance of heterogeneous RF-VLC network is analyzed and evaluated for two different configurations - aggregation and non-aggregation. To mitigate the power consumption overhead of VLC, a problem of minimizing the total power consumption of a general multi-user VLC indoor network while satisfying users traffic demands and maintaining an acceptable level of illumination is formulated. The optimization problem is solved by the efficient column generation algorithm. With ultra-low power consumption, VLC backscatter harvests energy from indoor light sources and transmits optical signals by modulating the reflected light from a reflector. A novel pixelated VLC backscatter is proposed and prototyped to address the limited modulation bandwidth by enabling more advanced modulation scheme than the state-of-the-art on-off keying (OOK) scheme and allowing for the first time orthogonal multiple access. VLC-based indoor access system is also suitable for indoor localization due to its unique properties, such as utilization of existing ubiquitous lighting infrastructure, high location and orientation accuracy, and no interruption to RF-based devices. A novel retroreflector-based visible light localization system is proposed and prototyped to establish an almost zero-delay backward channel using a retroreflector to reflect light back to its source. This system can localize passive IoT devices without requiring computation and heavy sensing (e.g., camera) at the device end

User Association Optimisation in HetNets: Algorithms and Performance

PhDThe fifth generation (5G) mobile networks expect significantly higher transmission rate and energy efficiency than existing networks. Heterogeneous networks (HetNets), where various low power base stations (BSs) are underlaid in a macro-cellular network, are likely to become the dominate theme during the wireless evolution towards 5G. However the complex HetNets scenario poses substantial challenges to the user association design. This thesis focuses on the user association optimisation for different HetNets scenarios. First, user association policy is designed for conventional grid-powered HetNets via game theory. An optimal user association algorithm is proposed to improve the downlink (DL) system performance. In order to address the uplink-downlink (UL-DL) asymmetry issue in HetNets, a joint UL and DL user association algorithm is further developed to enhance both UL and DL energy efficiencies. In addition, an opportunistic user association algorithm in multi-service HetNets is proposed for quality of service (QoS) provision of delay constraint traffic while providing fair resource allocation for best effort traffic. Second, driven by increasing environmental concerns, user association policy is designed for green HetNets with renewable energy powered BSs. In such a scenario, the proposed adaptive user association algorithm is able to adapt the user association decision to the amount of renewable energy harvested by BSs. Third, HetNets with hybrid energy sources are investigated, as BSs powered by both power grid and renewable energy sources have the superiority in supporting uninterrupted service as well as achieving green communications. In this context, an optimal user association algorithm is developed to achieve the tradeoffs between average traffic delay and on-grid energy consumption. Additionally, a two-dimensional optimisation on user association and green energy allocation is proposed to minimise both total and peak on-grid energy consumptions, as well as enhance the QoS provision. Thorough theoretical analysis is conducted in the development of all proposed algorithms, and performance of proposed algorithms is evaluated via comprehensive simulations

Energy aware management of 5G networks

Doctor of PhilosophyDepartment of Electrical and Computer EngineeringBalasubramaniam NatarajanThe number of wireless devices is predicted to skyrocket from about 5 billion in 2015 to 25 billion by 2020. Therefore, traffic volume demand is envisioned to explode in the very near future. The proposed fifth generation (5G) of mobile networks is expected to be a mixture of network components with different sizes, transmit powers, back-haul connections and radio access technologies. While there are many interesting problems within the 5G framework, we address the challenges of energy-related management in a heterogeneous 5G networks. Based on the 5G architecture, in this dissertation, we present some fundamental methodologies to analyze and improve the energy efficiency of 5G network components using mathematical tools from optimization, control theory and stochastic geometry. Specifically, the main contributions of this research include: • We design power-saving modes in small cells to maximize energy efficiency. We first derive performance metrics for heterogeneous cellular networks with sleep modes based on stochastic geometry. Then we quantify the energy efficiency and maximize it with quality-of-service constraint based on an analytical model. We also develop a simple sleep strategy to further improve the energy efficiency according to traffic conditions. • We conduct a techno-economic analysis of heterogeneous cellular networks powered by both on-grid electricity and renewable energy. We propose a scheme to minimize the electricity cost based on a real-time pricing model. • We provide a framework to uncover desirable system design parameters that offer the best gains in terms of ergodic capacity and average achievable throughput for device-to-device underlay cellular networks. We also suggest a two-phase scheme to optimize the ergodic capacity while minimizing the total power consumption. • We investigate the modeling and analysis of simultaneous information and energy transfer in Internet of things and evaluate both transmission outage probability and power outage probability. Then we try to balance the trade-off between the outage performances by careful design of the power splitting ratio. This research provides valuable insights related to the trade-offs between energy-conservation and system performance in 5G networks. Theoretical and simulation results help verify the performance of the proposed algorithms