81 research outputs found
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
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
Secrecy-Optimized Resource Allocation for Device-to-Device Communication Undelaying Cellular Networks
Lâobjectif principal de lâintroduction de la communication de pĂ©riphĂ©rique-Ă -pĂ©riphĂ©rique «device-to-device» (D2D) sous-jacente aux systĂšmes de communication sans fil de cinquiĂšme gĂ©nĂ©ration (5G), est dâaugmenter lâefficacitĂ© spectrale (ES). Cependant, la communication
D2D sous-jacente aux rĂ©seaux cellulaires peut entraĂźner une dĂ©gradation des performances causĂ©e par des co-interfĂ©rences de canal sĂ©vĂšres entre les liaisons cellulaires et D2D. De plus, en raison de la complexitĂ© du contrĂŽle et de la gestion, les connexions directes entre les appareils Ă proximitĂ© sont vulnĂ©rables. En consĂ©quence, la communication D2D nâest pas robuste contre les menaces de sĂ©curitĂ© et lâĂ©coute clandestine. Pourtant, les co-interfĂ©rences
de canal peuvent ĂȘtre adoptĂ©es pour aider les utilisateurs cellulaires (UC) et les paires D2D afin dâempĂȘcher lâĂ©coute clandestine. Dans cette thĂšse, nous Ă©tudions diffĂ©rents scĂ©narios de problĂšmes dâallocation de ressources en utilisant le concept de sĂ©curitĂ© de couche physique
«physical layer security» (PLS) pour la communication D2D sous-jacente aux rĂ©seaux cellulaires, tout en satisfaisant les exigences minimales de qualitĂ© de service (QoS) des liaisons cellulaires et D2D. Dans le cas oĂč PLS est pris en compte, lâinterfĂ©rence peut aider Ă rĂ©duire lâĂ©coute clandestine. PremiĂšrement, nous formulons un scĂ©nario dâallocation de ressources dans lequel chaque bloc de ressources (RB) temps-frĂ©quence de multiplexage par rĂ©partition orthogonale en frĂ©quence (OFDM) peut ĂȘtre partagĂ© par une seule CU et une paire D2D dans un rĂ©seau
unicellulaire. Le problĂšme formulĂ© est rĂ©duit au problĂšme de correspondance tridimensionnelle, qui est gĂ©nĂ©ralement NP-difficile, et la solution optimale peut ĂȘtre obtenue par des
mĂ©thodes compliquĂ©es, telles que la recherche par force brute et/ou lâalgorithme de branchement et de liaison qui ont une complexitĂ© de calcul exponentielle. Nous proposons donc une mĂ©ta-heuristique basĂ©e sur lâalgorithme de recherche tabou «Tabu Search» (TS) avec une complexitĂ© de calcul rĂ©duite pour trouver globalement la solution dâallocation de ressources radio quasi-optimale.----------ABSTRACT: The primary goal of introducing device-to-device (D2D) communication underlying fifthgeneration (5G) wireless communication systems is to increase spectral efficiency (ES). However, D2D communication underlying cellular networks can lead to performance degradation caused by severe co-channel interference between cellular and D2D links. In addition, due to the complexity of control and management, direct connections between nearby devices
are vulnerable. Thus, D2D communication is not robust against security threats and eavesdropping. On the other hand, the co-channel interference can be adopted to help cellular users (CUs) and D2D pairs to prevent eavesdropping. In this thesis, we investigate different resource allocation problem scenarios using the physical layer security (PLS) concept for the D2D communication underlying cellular networks, while satisfying the minimum quality of service (QoS) requirements of cellular and D2D link. If the PLS is taken into account, the interference can help reduce eavesdropping. First, we formulate a resource allocation scenario in which each orthogonal frequency-division
multiplexing (OFDM) time-frequency resource block (RB) can be shared by one single CU and one D2D pair in a single-cell network. The formulated problem is reduced to the threedimensional matching problem, which is generally NP-hard, and the optimal solution can be obtained through the complicated methods, such as brute-force search and/or branch-andbound algorithm that have exponential computational complexity. We, therefore, propose a meta-heuristic based on Tabu Search (TS) algorithm with a reduced computational complexity to globally find the near-optimal radio resource allocation solution
Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory
Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization
Perfomance Comparison of Genetic and Greedy Algorithms in Underlay Device-to-Device Communication
The number of cellular users (CU) continues to increase in Indonesia. This impacts a large network load for the number of devices connected to the main network so it will have an impact on the quality of service. Device-to-Device (D2D) communication as components for LTE-A technology enabling a direct wireless link between the CUs without routing the data via the evolved Node B (eNB) signal or the core network. The need for algorithm and power control used to allocate radio resources so it can get a good quality of service because of communications technology D2D. In this study, we analyze and compare the performance parameters of D2D communication systems, including system interference, system sum-rate, system spectral efficiency, total energy system, and system energy efficiency based on Genetic and Greedy Algorithms in allocating radio resources and controlling the power of users. The genetic algorithm works with three operators in allocating resource block (RB), including proportional selection, crossover, and mutation. This process is repeated many times to produce several generations so that the best allocation can be got. The genetic algorithm has a flexible number of D2D and cellular communications in several RBs, minimum signal to interference plus noise ratio (SINR) also considered for mobile communication in ensuring the quality of its services. Numerical evaluations demonstrate the superior performance of the Genetic Algorithm in terms of system power, energy efïŹciency, and interference mitigation. As repetition gets larger, the Genetic algorithm results in better spectral efficiency
Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks
Device to Device (D2D) Communication is one of the technology components of
the evolving 5G architecture, as it promises improvements in energy efficiency,
spectral efficiency, overall system capacity, and higher data rates. The above
noted improvements in network performance spearheaded a vast amount of research
in D2D, which have identified significant challenges that need to be addressed
before realizing their full potential in emerging 5G Networks. Towards this
end, this paper proposes the use of a distributed intelligent approach to
control the generation of D2D networks. More precisely, the proposed approach
uses Belief-Desire-Intention (BDI) intelligent agents with extended
capabilities (BDIx) to manage each D2D node independently and autonomously,
without the help of the Base Station. The paper includes detailed algorithmic
description for the decision of transmission mode, which maximizes the data
rate, minimizes the power consumptions, while taking into consideration the
computational load. Simulations show the applicability of BDI agents in jointly
solving D2D challenges.Comment: 10 pages,9 figure
Optimal Video Streaming in Dense 5G Networks With D2D Communications
© 2017 IEEE. Mobile video traffic and mobile devices have now outpaced other data traffic and fixed devices. Global service providers are attempting to propose new mobile infrastructures and solutions for high performance of video streaming services, i.e., high quality of experience (QoE) at high resource efficiency. Although device-to-device (D2D) communications have been an emerging technique that is anticipated to provide a massive number of mobile users with advanced services in 5G networks, the management of resource and co-channel interference between D2D pairs, i.e., helper-requester pairs, and cellular users (CUs) is challenging. In this paper, we design an optimal rate allocation and description distribution for high performance video streaming, particularly, achieving high QoE at high energy efficiency while limiting co-channel interference over D2D communications in 5G networks. To this end, we allocate optimal encoding rates to different layers of a video segment and then packetize the video segment into multiple descriptions with embedded forward error correction before transmission. Simultaneously, the optimal numbers of descriptions are distributed to D2D helpers and base stations in a cooperative scheme for transmitting to the D2D requesters. The optimal results are efficiently in correspondence with intra-popularity of different segments of a video characterized by requesters' behavior, characteristic of lossy wireless channels, channel state information of D2D requesters, and constraints on remaining energy of D2D helpers and target signal to interference plus noise ratio of CUs. Simulation results demonstrate the benefits of our proposed solution in terms of high performance video streaming
Survey on the state-of-the-art in device-to-device communication: A resource allocation perspective
Device to Device (D2D) communication takes advantage of the proximity between the communicating devices in order to achieve efficient resource utilization, improved throughput and energy efficiency, simultaneous serviceability and reduced latency. One of the main characteristics of D2D communication is reuse of the frequency resource in order to improve spectral efficiency of the system. Nevertheless, frequency reuse introduces significantly high interference levels thus necessitating efficient resource allocation algorithms that can enable simultaneous communication sessions through effective channel and/or power allocation. This survey paper presents a comprehensive investigation of the state-of-the-art resource allocation algorithms in D2D communication underlaying cellular networks. The surveyed algorithms are evaluated based on heterogeneous parameters which constitute the elementary features of a resource allocation algorithm in D2D paradigm. Additionally, in order to familiarize the readers with the basic design of the surveyed resource allocation algorithms, brief description of the mode of operation of each algorithm is presented. The surveyed algorithms are divided into four categories based on their technical doctrine i.e., conventional optimization based, Non-Orthogonal-MultipleAccess (NOMA) based, game theory based and machine learning based techniques. Towards the end, several open challenges are remarked as the future research directions in resource allocation for D2D communication
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
- âŠ