Mobility and resource management for 5G heterogeneous networks

The conventional topology of current cellular networks is a star structure, where central control points usually serve as base stations (BSs). This provides the advantage of simplicity while still providing quality of service (QoS). For next-generation networks, however, this topology is disadvantageous and difficult to use due to the insufficient availability of network access. The hybrid topology radio network will thus naturally be the future mobile access network that can help to overcome current and future challenges efficiently. Therefore, relay technology can play an important role in a hybrid cellular network topology. Today, with the recent long-term evolution-advanced (LTE-A) standards, the 3rd Generation Partnership Project (3GPP) supports a single-hop relay technology in which the radio access link between the BS and users is relayed by only one relay station (RS). With the help of multi-hop relay, however, the radio link between the BS and users can be extended to more than two hops to improve the coverage and network capacity. Multiple hops to transmit data to and from the corresponding BS results in the reduction of path loss. However, using a multi-hop relay system requires more radio resources to transmit data through different hops. More interference is also created due to a greater number of simultaneous transmissions in the network. New mobility and resource management schemes are thus important for achieving a high QoS while increasing the whole network capacity. In the first part, the problem of relay selection and radio resource allocation is studied, and choosing how the bandwidth should be shared between direct, backhaul, and access links in multi-hop relay networks is discussed. In such a network, resource allocation plays a critical role because it manages channel access in both time and frequency domains and determines how resources are allocated for different links. The proposed solution includes a nonlinear programming technique and a heuristic method. First, the problem formulation of resource allocation and relay selection is presented to provide an integrated framework for multi-hop relay networks. Second, an analytical solution to the problem is presented using a nonlinear programming technique. Finally, an iterative two-stage algorithm is presented to address the joint resource allocation and relay selection problem in multi-hop relay networks Under backhaul and capacity limitation constraints. In particular, the first stage proposed a fast approximation analytical solution for a resource allocation algorithm that takes into account the trade-off between the optimality and the complexity of the multi-hop relay architecture; the second stage presented a heuristic relay selection strategy that considers the RS load and helps to keep the relay from being overloaded is proposed. In the second part, the mobility problem in downlink multi-hop relay networks is addressed. In addition to the resource allocation issue, the relay selection problem is studied from a network layer perspective. Therefore, this part includes the issue of radio path selection. As an alternative to the heuristic algorithm developed in the previous part, the presented work describes the development and evaluation of a relay-selection scheme based on a Markov decision process (MDP) that considers the RS load and the existing radio-link path to improve handoff performance. First, the problem formulation of resource allocation and relay selection is presented. Second, an MDP mathematical model is developed to solve the relay selection problem in a decentralized way and to make the selection process simple. This relay selection scheme has the objective of maintaining the throughput and ensuring seamless mobility and service continuity to all mobile terminals while reducing the handoff frequency and improving handoff performance. In the third part, the admission and power control problem of a general heterogeneous network (HetNet) consisting of several small cells (SCs) is solved. Compared to the first two parts of this work, the system is expanded from a multi-hop RS to a general SC context. This part therefore focuses only on the access link problem, assuming the capacity of the SC backhaul links are large enough not to be bottlenecks. This part mainly deals with the problem of how to maximize the number of admitted users in an overloaded system while minimizing the transmit power given a certain QoS level. First, the problem is formulated to address concerns about QoS requirements in a better way. Second, a Voronoi-based user association scheme for maximizing the number of admitted users in the system under QoS and capacity limitation constraints is proposed to find near-optimal solutions. Finally, a twostage algorithm is presented to address the joint admission and power control problem in a downlink heterogeneous SC network. In particular, the first stage proposes a dynamic call admission control policy that considers the SC load and call-level QoS while also helping to keep the system from being overloaded. The second stage presents an adaptive power allocation strategy that considers both user distribution and the density of SCs in HetNets. Finally, the proposed solutions are evaluated using extensive numerical simulations, and the numerical results are presented to provide a comparison with related works found in the literature

Delay QoS Provisioning and Optimal Resource Allocation for Wireless Networks

Recent years have witnessed a significant growth in wireless communication and networking due to the exponential growth in mobile applications and smart devices, fueling unprecedented increase in both mobile data traffic and energy demand. Among such data traffic, real-time data transmissions in wireless systems require certain quality of service (QoS) constraints e.g., in terms of delay, buffer overflow or packet drop/loss probabilities, so that acceptable performance levels can be guaranteed for the end-users, especially in delay sensitive scenarios, such as live video transmission, interactive video (e.g., teleconferencing), and mobile online gaming. With this motivation, statistical queuing constraints are considered in this thesis, imposed as limitations on the decay rate of buffer overflow probabilities. In particular, the throughput and energy efficiency of different types of wireless network models are analyzed under QoS constraints, and optimal resource allocation algorithms are proposed to maximize the throughput or minimize the delay. In the first part of the thesis, the throughput and energy efficiency analysis for hybrid automatic repeat request (HARQ) protocols are conducted under QoS constraints. Approximations are employed for small QoS exponent values in order to obtain closed-form expressions for the throughput and energy efficiency metrics. Also, the impact of random arrivals, deadline constraints, outage probability and QoS constraints are studied. For the same system setting, the throughput of HARQ system is also analyzed using a recurrence approach, which provides more accurate results for any value of the QoS exponent. Similarly, random arrival models and deadline constraints are considered, and these results are further extended to the finite-blocklength coding regime. Next, cooperative relay networks are considered under QoS constraints. Specifically, the throughput performance in the two-hop relay channel, two-way relay channel, and multi-source multi-destination relay networks is analyzed. Finite-blocklength codes are considered for the two-hop relay channel, and optimization over the error probabilities is investigated. For the multi-source multi-destination relay network model, the throughput for both cases of with and without CSI at the transmitter sides is studied. When there is perfect CSI at the transmitter, transmission rates can be varied according to instantaneous channel conditions. When CSI is not available at the transmitter side, transmissions are performed at fixed rates, and decoding failures lead to retransmission requests via an ARQ protocol. Following the analysis of cooperative networks, the performance of both half-duplex and full-duplex operations is studied for the two-way multiple input multiple output (MIMO) system under QoS constraints. In full-duplex mode, the self-interference inflicted on the reception of a user due to simultaneous transmissions from the same user is taken into account. In this setting, the system throughput is formulated by considering the sum of the effective capacities of the users in both half-duplex and full-duplex modes. The low signal to noise ratio (SNR) regime is considered and the optimal transmission/power-allocation strategies are characterized by identifying the optimal input covariance matrices. Next, mode selection and resource allocation for device-to-device (D2D) cellular networks are studied. As the starting point, ransmission mode selection and resource allocation are analyzed for a time-division multiplexed (TDM) cellular network with one cellular user, one base station, and a pair of D2D users under rate and QoS constraints. For a more complicated setting with multiple cellular and D2D users, two joint mode selection and resource allocation algorithms are proposed. In the first algorithm, the channel allocation problem is formulated as a maximum-weight matching problem, which can be solved by employing the Hungarian algorithm. In the second algorithm, the problem is divided into three subproblems, namely user partition, power allocation and channel assignment, and a novel three-step method is proposed by combining the algorithms designed for the three subproblems. In the final part of the thesis, resource allocation algorithms are investigated for content delivery over wireless networks. Three different systems are considered. Initially, a caching algorithm is designed, which minimizes the average delay of a single-cell network. The proposed algorithm is applicable in settings with very general popularity models, with no assumptions on how file popularity varies among different users, and this algorithm is further extended to a more general setting, in which the system parameters and the distributions of channel fading change over time. Next, for D2D cellular networks operating under deadline constraints, a scheduling algorithm is designed, which manages mode selection, channel allocation and power maximization with acceptable complexity. This proposed scheduling algorithm is designed based on the convex delay cost method for a D2D cellular network with deadline constraints in an OFDMA setting. Power optimization algorithms are proposed for all possible modes, based on our utility definition. Finally, a two-step intercell interference (ICI)-aware scheduling algorithm is proposed for cloud radio access networks (C-RANs), which performs user grouping and resource allocation with the goal of minimizing delay violation probability. A novel user grouping algorithm is developed for the user grouping step, which controls the interference among the users in the same group, and the channel assignment problem is formulated as a maximum-weight matching problem in the second step, which can be solved using standard algorithms in graph theory

Optimization Framework and Graph-Based Approach for Relay-Assisted Bidirectional OFDMA Cellular Networks

This paper considers a relay-assisted bidirectional cellular network where the base station (BS) communicates with each mobile station (MS) using OFDMA for both uplink and downlink. The goal is to improve the overall system performance by exploring the full potential of the network in various dimensions including user, subcarrier, relay, and bidirectional traffic. In this work, we first introduce a novel three-time-slot time-division duplexing (TDD) transmission protocol. This protocol unifies direct transmission, one-way relaying and network-coded two-way relaying between the BS and each MS. Using the proposed three-time-slot TDD protocol, we then propose an optimization framework for resource allocation to achieve the following gains: cooperative diversity (via relay selection), network coding gain (via bidirectional transmission mode selection), and multiuser diversity (via subcarrier assignment). We formulate the problem as a combinatorial optimization problem, which is NP-complete. To make it more tractable, we adopt a graph-based approach. We first establish the equivalence between the original problem and a maximum weighted clique problem in graph theory. A metaheuristic algorithm based on any colony optimization (ACO) is then employed to find the solution in polynomial time. Simulation results demonstrate that the proposed protocol together with the ACO algorithm significantly enhances the system total throughput.Comment: 27 pages, 8 figures, 2 table

Joint Source and Relay Precoding Designs for MIMO Two-Way Relaying Based on MSE Criterion

Properly designed precoders can significantly improve the spectral efficiency of multiple-input multiple-output (MIMO) relay systems. In this paper, we investigate joint source and relay precoding design based on the mean-square-error (MSE) criterion in MIMO two-way relay systems, where two multi-antenna source nodes exchange information via a multi-antenna amplify-and-forward relay node. This problem is non-convex and its optimal solution remains unsolved. Aiming to find an efficient way to solve the problem, we first decouple the primal problem into three tractable sub-problems, and then propose an iterative precoding design algorithm based on alternating optimization. The solution to each sub-problem is optimal and unique, thus the convergence of the iterative algorithm is guaranteed. Secondly, we propose a structured precoding design to lower the computational complexity. The proposed precoding structure is able to parallelize the channels in the multiple access (MAC) phase and broadcast (BC) phase. It thus reduces the precoding design to a simple power allocation problem. Lastly, for the special case where only a single data stream is transmitted from each source node, we present a source-antenna-selection (SAS) based precoding design algorithm. This algorithm selects only one antenna for transmission from each source and thus requires lower signalling overhead. Comprehensive simulation is conducted to evaluate the effectiveness of all the proposed precoding designs.Comment: 32 pages, 10 figure

Bio-Inspired Resource Allocation for Relay-Aided Device-to-Device Communications

The Device-to-Device (D2D) communication principle is a key enabler of direct localized communication between mobile nodes and is expected to propel a plethora of novel multimedia services. However, even though it offers a wide set of capabilities mainly due to the proximity and resource reuse gains, interference must be carefully controlled to maximize the achievable rate for coexisting cellular and D2D users. The scope of this work is to provide an interference-aware real-time resource allocation (RA) framework for relay-aided D2D communications that underlay cellular networks. The main objective is to maximize the overall network throughput by guaranteeing a minimum rate threshold for cellular and D2D links. To this direction, genetic algorithms (GAs) are proven to be powerful and versatile methodologies that account for not only enhanced performance but also reduced computational complexity in emerging wireless networks. Numerical investigations highlight the performance gains compared to baseline RA methods and especially in highly dense scenarios which will be the case in future 5G networks.Comment: 6 pages, 6 figure