Algorithms for multi-trip vehicle routing and device to device communications

Motivated by the transportation needs of modern-day retailers, we consider a variant of the vehicle routing problem with time windows in which each truck has a variable capacity. In our model, each vehicle can bring one or more wagons. The clients are visited within specified time windows, and the vehicles can also make multiple trips. We give a math- ematical programming formulation for the problem and a branch and price algorithm is used to solve the model. In each iteration of branch and price, column generation is ap- plied. Based on the different capacities, different subproblems are created to find the best column. We extend Solomon’s instances to evaluate our approach. We report on the com- putational results using concert technology in CPLEX. Ours is the first such study to the best of our knowledge. For the second part of the thesis, we study the sharing of spec- trum in the device-to-device (D2D) communications in an underlay cellular network. Our model maximizes the total sum-rate such that i) each D2D link is assigned at most one sub-channel, ii) the total interference is at most the required maximum. Our model can also minimize the interference subject to i) the total sum-rate being bounded by some required amount. We give a branch-n-cut algorithm for solving both models. We give a Lagrangian relaxation which is solved optimally and combinatorially for the minimization objective. We give an iterative rounding algorithm that achieves at least a quarter of the optimal sum rate and no more than the required maximum of the total interference when the objective is to maximize sum-rate. Detailed experiments are performed on synthetic as well as net- work simulator data. Our experiments establish the effectiveness of the branch-n-cut and the iterative rounding approach for channel assignment. This thesis is a study on the use of branch and cut, branch and price, and iterative rounding for solving two real world optimization problems.NSER

Resource Allocation Management of D2D Communications in Cellular Networks

To improve the system capacity, spectral performance, and energy efficiency, stringent requirements for increasing reliability, and decreasing delays have been intended for next-generation wireless networks. Device-to-device (D2D) communication is a promising technique in the fifth-generation (5G) wireless communications to enhance spectral efficiency, reduce latency and energy efficiency. In D2D communication, two wireless devices in close proximity can communicate with each other directly without pass through the Base Station (BS) or Core Network (CN). In this proposal, we identify compromises and challenges of integrating D2D communications into cellular networks and propose potential solutions. To maximize gains from such integration, resource management, and interference avoidance are key factors. Thus, it is important to properly allocate resources to guarantee reliability, data rate, and increase the capacity in cellular networks. In this thesis, we address the problem of resource allocation in D2D communication underlaying cellular networks. We provide a detailed review of the resource allocation problem of D2D communications. My Ph.D research will tackle several issues in order to alleviate the interference caused by a D2D user-equipment (DUE) and cellular-userequipment (CUE) in uplink multi-cell networks, the intra-cell and inter-cell interference are considered in this work to improve performance for D2D communication underlaying cellular networks. The thesis consists of four main results. First, the preliminary research proposes a resource allocation scheme to formulate the resource allocation problem through optimization of the utility function, which eventually reflects the system performance concerning network throughput. The formulated optimization problem of maximizing network throughput while guaranteeing predefined service levels to cellular users is non-convex and hence intractable. Thus, the original problem is broken down into two stages. The first stage is the admission control of D2D users while the second one is the power control for each admissible D2D pair and its reuse partner. Second, we proposed a spectrum allocation framework based on Reinforcement Learning (RL) for joint mode selection, channel assignment, and power control in D2D communication. The objective is to maximize the overall throughput of the network while ensuring the quality of transmission and guaranteeing low latency requirements of D2D communications. The proposed algorithm uses reinforcement learning (RL) based on Markov Decision Process (MDP) with a proposed new reward function to learn the policy by interacting with the D2D environment. An Actor-Critic Reinforcement Learning (AC-RL) approach is then used to solve the resource management problem. The simulation results show that our learning method performs well, can greatly improve the sum rate of D2D links, and converges quickly, compared with the algorithms in the literature. Third, a joint channel assignment, power allocation and resource allocation algorithm is proposed. The algorithm designed to allow multiple DUEs to reuse the same CUE channel for D2D communications underlaying multi-cell cellular networks with the consideration of the inter-cell and intra-cell interferences. Obviously, under satisfying the QoS requirements of both DUEs and CUEs, the more the number of the allowed accessing DUEs on a single CUE channel is, the higher the spectrum efficiency is, and the higher the network throughput can be achieved. Meanwhile, implementing resource allocation strategies at D2D communications allows to effectively mitigate the interference caused by the D2D communications at both cellular and D2D users. In this part, the formulated optimization problem of maximizing network throughput while guaranteeing predefined service levels to cellular users. Therefore, we propose an algorithm that solves this nonlinear mixed-integer problem in three steps wherein the first step, subchannel assignment is carried out, the second one is the power allocation, while the third step of the proposed algorithm is the resource allocation for multiple D2D pairs based on genetic algorithm. The simulation results verify the effectiveness of our proposed algorithm. Fourth, integrating D2D communications and Femtocells in Heterogeneous Networks (HetNets) is a promising technology for future cellular networks. Which have attracted a lot of attention since it can significantly improve the capacity, energy efficiency and spectral performance of next-generation wireless networks (5G). D2D communication and femtocell are introduced as underlays to the cellular systems by reusing the cellular channels to maximize the overall throughput in the network. In this part, the problem is formulated to maximize the network throughput under the QoS constraints for CUEs, DUEs and FUEs. This problem is a mixed-integer non-linear problem that is difficult to be solved directly. To solve this problem, we propose a joint channel selection, power control, and resource allocation scheme to maximize the sum rate of the cellular network system. The simulation results show that the proposed scheme can effectively reduce the computational complexity and improve the overall system throughput compared with existing well-known methods

Opportunistic device-to-device communication in cellular networks: from theory to practice

Mención Internacional en el título de doctorCellular service providers have been struggling with users’ demand since the emergence of mobile Internet. As a result, each generation of cellular network prevailed over its predecessors mainly in terms of connection speed. However, the fifth generation (5G) of cellular network promises to go beyond this trend by revolutionizing the network architecture. Device-to-Device (D2D) communication is one of the revolutionary changes that enables mobile users to communicate directly without traversing a base station. This feature is being actively studied in 3GPP with special focus on public safety as it allows mobiles to operate in adhoc mode. Although under the (partial) control of the network, D2D communications open the door to many other use-cases. This dissertation studies different aspects of D2D communications and its impact on the key performance indicators of the network. We design an architecture for the collaboration of cellular users by means of timely exploited D2D opportunities. We begin by presenting the analytical study on opportunistic outband D2D communications. The study reveals the great potential of opportunistic outband D2D communications for enhancing energy efficiency, fairness, and capacity of cellular networks when groups of D2D users can be form and managed in the cellular network. Then we introduce a protocol that is compatible with the latest release of IEEE and 3GPP standards and allows for implementation of our proposal in a today’s cellular network. To validate our analytical findings, we use our experimental Software Defined Radio (SDR)-based testbed to further study our proposal in a real world scenario. The experimental results confirm the outstanding potential of opportunistic outband D2D communications. Finally, we investigate the performance merits and disadvantages of different D2D “modes”. Our investigation reveals, despite the common belief, that all D2D modes are complementary and their merits are scenario based.This work has been supported by IMDEA Networks Institute.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Douglas Leith.- Secretario: Albert Banchs Roca.- Vocal: Carla Fabiana Chiasserin

Reduced complexity optimal resource allocation for enhanced video quality in a heterogeneous network environment

The latest Heterogeneous Network (HetNet) environments, supported by 5th generation (5G) network solutions, include small cells deployed to increase the traditional macrocell network performance. In HetNet environments, before data transmission starts, there is a user association (UA) process with a specific base station (BS). Additionally, during data transmission, diverse resource allocation (RA) schemes are employed. UA-RA solutions play a critical role in improving network load balancing, spectral performance, and energy efficiency. Although several studies have examined the joint UA-RA problem, there is no optimal strategy to address it with low complexity while also reducing the time overhead. We propose two different versions of simulated annealing (SA): Reduced Search Space SA (RS3A) and Performance-Improved Reduced Search Space SA (P IRS3A), algorithms for solving UA-RA problem in HetNets. First, the UA-RA problem is formulated as a multiple knapsack problem (MKP) with constraints on the maximum BS capacity and transport block size (TBS) index. Second, the proposed RS3A and P IRS3A are used to solve the formulated MKP. Simulation results show that the proposed scheme P IRS3A outperforms RS3A and other existing schemes such as Default Simulated Annealing (DSA), and Default Genetic Algorithm (DGA) in terms of variability and DSA and RS3A in terms of Quality of Service (QoS) metrics, including throughput, packet loss ratio (PLR), delay and jitter. Simulation results show that P IRS3A generates solutions that are very close to the optimal solution

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Resource Allocation in Multi-user MIMO Networks: Interference Management and Cooperative Communications

Nowadays, wireless communications are becoming so tightly integrated in our daily lives, especially with the global spread of laptops, tablets and smartphones. This has paved the way to dramatically increasing wireless network dimensions in terms of subscribers and amount of flowing data. Therefore, the two important fundamental requirements for the future 5G wireless networks are abilities to support high data traffic and exceedingly low latency. A likely candidate to fulfill these requirements is multicell multi-user multi-input multiple-output (MU-MIMO); also termed as coordinated multi-point (CoMP) transmission and reception. To achieve the highest possible performance in MU-MIMO networks, a properly designed resource allocation algorithm is needed. Moreover, with the rapidly growing data traffic, interference has become a major limitation in wireless networks. Interference alignment (IA) has been shown to significantly manage the interference and improve the network performance. However, how practically use IA to mitigate interference in a downlink MU-MIMO network still remains an open problem. In this dissertation, we improve the performance of MU-MIMO networks in terms of spectral efficiency, by designing and developing new beamforming algorithms that can efficiently mitigate the interference and allocate the resources. Then we mathematically analyze the performance improvement of MUMIMO networks employing proposed techniques. Fundamental relationships between network parameters and the network performance is revealed, which provide guidance on the wireless networks design. Finally, system level simulations are conducted to investigate the performance of the proposed strategies