Priority-Based Resource Allocation for Downlink OFDMA Systems Supporting RT and NRT Traffics

Efficient radio resource management is essential in Quality-of-Service (QoS) provisioning for wireless communication networks. In this paper, we propose a novel priority-based packet scheduling algorithm for downlink OFDMA systems. The proposed algorithm is designed to support heterogeneous applications consisting of both real-time (RT) and non-real-time (NRT) traffics with the objective to increase the spectrum efficiency while satisfying diverse QoS requirements. It tightly couples the subchannel allocation and packet scheduling together through an integrated cross-layer approach in which each packet is assigned a priority value based on both the instantaneous channel conditions as well as the QoS constraints. An efficient suboptimal heuristic algorithm is proposed to reduce the computational complexity with marginal performance degradation compared to the optimal solution. Simulation results show that the proposed algorithm can significantly improve the system performance in terms of high spectral efficiency and low outage probability compared to conventional packet scheduling algorithms, thus is very suitable for the downlink of current OFDMA systems

A heuristic for fair dynamic resource allocation in over-loaded OFDMA systems

OFDMA is a popular coding scheme for mobile wireless communications. In OFDMA, one must allocate the available resources (bandwidth and power) dynamically, as user requests arrive and depart in a stochastic manner. Several exact and heuristic methods exist to do this, but they all perform poorly in the “over-loaded” case, in which the user demand is close to or exceeds the system capacity. To address this case, we present a dynamic local search heuristic. A particular feature of our heuristic is that it takes fairness into consideration. Simulations on realistic data show that our heuristic is fast enough to be used in real-time, and consistently delivers allocations of good quality

Load balancing using cell range expansion in LTE advanced heterogeneous networks

The use of heterogeneous networks is on the increase, fueled by consumer demand for more data. The main objective of heterogeneous networks is to increase capacity. They offer solutions for efficient use of spectrum, load balancing and improvement of cell edge coverage amongst others. However, these solutions have inherent challenges such as inter-cell interference and poor mobility management. In heterogeneous networks there is transmit power disparity between macro cell and pico cell tiers, which causes load imbalance between the tiers. Due to the conventional user-cell association strategy, whereby users associate to a base station with the strongest received signal strength, few users associate to small cells compared to macro cells. To counter the effects of transmit power disparity, cell range expansion is used instead of the conventional strategy. The focus of our work is on load balancing using cell range expansion (CRE) and network utility optimization techniques to ensure fair sharing of load in a macro and pico cell LTE Advanced heterogeneous network. The aim is to investigate how to use an adaptive cell range expansion bias to optimize Pico cell coverage for load balancing. Reviewed literature points out several approaches to solve the load balancing problem in heterogeneous networks, which include, cell range expansion and utility function optimization. Then, we use cell range expansion, and logarithmic utility functions to design a load balancing algorithm. In the algorithm, user and base station associations are optimized by adapting CRE bias to pico base station load status. A price update mechanism based on a suboptimal solution of a network utility optimization problem is used to adapt the CRE bias. The price is derived from the load status of each pico base station. The performance of the algorithm was evaluated by means of an LTE MATLAB toolbox. Simulations were conducted according to 3GPP and ITU guidelines for modelling heterogeneous networks and propagation environment respectively. Compared to a static CRE configuration, the algorithm achieved more fairness in load distribution. Further, it achieved a better trade-off between cell edge and cell centre user throughputs. [Please note: this thesis file has been deferred until December 2016

Optimal resource allocation In base stations for mobile wireless communications

Telecommunications provides a rich source of interesting and often challenging optimisation problems. This thesis is concerned with a series of mixed-integer non-linear optimisation problems that arise in mobile wireless communications systems. The problems under consideration arise when mobile base stations have an Orthogonal Frequency-Division Multiple Access (OFDMA) architecture, where there are subcarriers for data transmission and users with various transmission demands. In such systems, we simultaneously allocate subcarriers to users and power to subcarriers, subject to various constraints including certain quality of service (QoS) constraints called rate constraints. These problems can be modelled as Mixed Integer Non-linear Programmes (MINLP). When we began the dissertation, we had the following main aims: To design an exact algorithm for the subcarrier and power allocation problem with rate constraints (SPARC), the objective of which is to maximise total data transmission rate of the entire system. To design an exact algorithm for the fractional subcarrier and power allocation problem with rate constraints (F-SPARC) problem in order to maximise system efficiency, i.e.: total data transmission rate divided by total power supplied to the system. To design a heuristic algorithm for the F-SPARC problem. To design a heuristic algorithm for the SPARC problem in dynamic settings, where user demand changes very frequently. Along the way, however, we discovered a new approach to a broad family of problems, which includes the F-SPARC as a special case. These problems are called mixed-integer fractional programs with indicator variables, and they are dealt with in Chapter 3

Efficient Scheduling Algorithms for Wireless Resource Allocation and Virtualization in Wireless Networks

The continuing growth in demand for better mobile broadband experiences has motivated rapid development of radio-access technologies to support high data rates and improve quality of service (QoS) and quality of experience (QoE) for mobile users. However, the modern radio-access technologies pose new challenges to mobile network operators (MNO) and wireless device designers such as reducing the total cost of ownership while supporting high data throughput per user, and extending battery life-per-charge of the mobile devices. In this thesis, a variety of optimization techniques aimed at providing innovative solutions for such challenges are explored. The thesis is divided into two parts. In the first part, the challenge of extending battery life-per-charge is addressed. Optimal and suboptimal power-efficient schedulers that minimize the total transmit power and meet the QoS requirements of the users are presented. The second outlines the benefits and challenges of deploying wireless resource virtualization (WRV) concept as a promising solution for satisfying the growing demand for mobile data and reducing capital and operational costs. First, a WRV framework is proposed for single cell zone that is able to centralize and share the spectrum resources between multiple MNOs. Consequently, several WRV frameworks are proposed, which virtualize the spectrum resource of the entire network for cloud radio access network (C-RAN)- one of the front runners for the next generation network architecture. The main contributions of this thesis are in designing optimal and suboptimal solutions for the aforementioned challenges. In most cases, the optimal solutions suffer from high complexity, and therefore low-complexity suboptimal solutions are provided for practical systems. The optimal solutions are used as benchmarks for evaluating the suboptimal solutions. The results prove that the proposed solutions effectively contribute in addressing the challenges caused by the demand for high data rates and power transmission in mobile networks

Radio resource allocation for multicarrier-low density spreading multiple access

Multicarrier-low density spreading multiple access (MC-LDSMA) is a promising multiple access technique that enables near optimum multiuser detection. In MC-LDSMA, each user’s symbol spread on a small set of subcarriers, and each subcarrier is shared by multiple users. The unique structure of MC-LDSMA makes the radio resource allocation more challenging comparing to some well-known multiple access techniques. In this paper, we study the radio resource allocation for single-cell MC-LDSMA system. Firstly, we consider the single-user case, and derive the optimal power allocation and subcarriers partitioning schemes. Then, by capitalizing on the optimal power allocation of the Gaussian multiple access channel, we provide an optimal solution for MC-LDSMA that maximizes the users’ weighted sum-rate under relaxed constraints. Due to the prohibitive complexity of the optimal solution, suboptimal algorithms are proposed based on the guidelines inferred by the optimal solution. The performance of the proposed algorithms and the effect of subcarrier loading and spreading are evaluated through Monte Carlo simulations. Numerical results show that the proposed algorithms significantly outperform conventional static resource allocation, and MC-LDSMA can improve the system performance in terms of spectral efficiency and fairness in comparison with OFDMA

Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has aroused. Specifically, UAVs can be used in cellular networks as aerial users for delivery, surveillance, rescue search, or as an aerial base station (aBS) for communication with ground users in remote uncovered areas or in dense environments requiring prompt high capacity. Aiming to satisfy the high requirements of wireless aerial networks, several multiple access techniques have been investigated. In particular, space-division multiple access(SDMA) and power-domain non-orthogonal multiple access (NOMA) present promising multiplexing gains for aerial downlink and uplink. Nevertheless, these gains are limited as they depend on the conditions of the environment. Hence, a generalized scheme has been recently proposed, called rate-splitting multiple access (RSMA), which is capable of achieving better spectral efficiency gains compared to SDMA and NOMA. In this paper, we present a comprehensive survey of key multiple access technologies adopted for aerial networks, where aBSs are deployed to serve ground users. Since there have been only sporadic results reported on the use of RSMA in aerial systems, we aim to extend the discussion on this topic by modelling and analyzing the weighted sum-rate performance of a two-user downlink network served by an RSMA-based aBS. Finally, related open issues and future research directions are exposed.Comment: 16 pages, 6 figures, submitted to IEEE Journa

Algoritam alokacije resursa s dinamičkim pridruživanjem podnosioca u bežičnim mrežama zasnovanim na OFDMA-u

The allocation of available resources is one of the main issues in multi-user systems. Dependence of system capacity on radio link quality is an additional obstacle of efficient resource allocation in wireless networks. Combinations of two opposite approaches -- fair resource allocation and system capacity maximization are used to solve this problem in practice.This paper proposes a resource allocation method that is primarily based on assigning almost an equal bandwidth to all users. System capacity maximization is achieved by selecting the subcarriers with the best SNR values. This algorithm was developed for orthogonal frequency division multiple access (OFDMA) wireless systems. Resource allocation is done at the subcarrier level according to the weight factor that had been calculated for each user. Frequency hopping was used to increase frequency diversity and to make the system more robust to disturbance. Frequency hopping pattern is determined dynamically on the basis of SNR value of each subcarrier.The results of the proposed algorithm are compared with the water filling (WF) and proportional fairness (PF) methods. The influence of various data traffic classes on system throughput and resource allocation is also described.U sustavima s više korisnika jedno od glavnih pitanja je kako podijeliti raspoložive resurse. Kod radio mreža dodatni otežavajući faktor predstavlja promjenjivost kapaciteta sustava ovisno o kvaliteti radio veze. U praksi se za raspodjelu resursaobično koriste algoritmi koji su kombinacija dvaju oprečnih pristupa, fer raspodjele resursa i maksimizacije kapaciteta sustava.U ovom radu predložena je metoda primarno bazirana na fer raspodjeli resursa. Maksimizacija kapaciteta sustava ostvarena je odabirom podnosilaca s najboljim mogućim SNR-om. Algoritam je razvijen za sustave bazirane na OFDMA. Dodjela resursa korisnicima vrši se na razini pojedinog podnosioca prema izračunatom težinskom faktoru za svakog korisnika posebno. Kako bi se povećao frekvencijski diverziti i sustav učinio otpornijim na smetnje, uvedeno je frekvencijsko skakanje prema dinamički određenom predlošku. Predložak se formira na osnovu SNRvrijednosti određene po svakom podnosiocu. Rezultati predloženog algoritma uspoređeni su s WF (water filling) i PF(proportional fairness) algoritmima. Prikazan je utjecaj različitih klasa prometa na prijenosni kapacitet i raspodjelu resursa sustava