Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks

The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter

Energy efficient OFDMA networks maintaining statistical QoS guarantees for delay-sensitive traffic

An energy-efficient design is proposed under specific statistical quality-of-service (QoS) guarantees for delay-sensitive traffic in the downlink orthogonal frequency-division multiple access (OFDMA) networks. This design is based on Wu’s effective capacity (EC) concept [1], which characterizes the maximum throughput of a system subject to statistical delay-QoS requirements at the data-link layer. In the particular context considered, our main contributions consist of quantifying the effective energy-efficiency (EEE)-versus-EC tradeoff and characterizing the delay sensitive traffic as a function of the QoS-exponent ?, which expresses the exponential decay rate of the delay-QoS violation probabilities. Upon exploiting the properties of fractional programming, the originally quasi-concave EEE optimization problem having a fractional form is transformed into a subtractive optimization problem by applying Dinkelbach’s method. As a result, an iterative inner-outer loop based resource allocation algorithm is conceived for efficiently solving the transformed EEE optimization problem. Our simulation results demonstrate that the proposed scheme converges within a few Dinkelbach iterations to the desired solution accuracy. Furthermore, the impact of the circuitry power, of the QoS-exponent and of the power amplifier inefficiency is characterized numerically. These results reveal that the optimally allocated power maximizing the EEE decays exponentially with respect to both the circuitry power and the QoS-exponent, whilst decaying linearly with respect to the power amplifier inefficiency

Resource allocation in networks via coalitional games

The main goal of this dissertation is to manage resource allocation in network engineering problems and to introduce efficient cooperative algorithms to obtain high performance, ensuring fairness and stability. Specifically, this dissertation introduces new approaches for resource allocation in Orthogonal Frequency Division Multiple Access (OFDMA) wireless networks and in smart power grids by casting the problems to the coalitional game framework and by providing a constructive iterative algorithm based on dynamic learning theory.  Software Engineering (Software)Algorithms and the Foundations of Software technolog

Energy-Aware Competitive Power Allocation for Heterogeneous Networks Under QoS Constraints

This work proposes a distributed power allocation scheme for maximizing energy efficiency in the uplink of orthogonal frequency-division multiple access (OFDMA)-based heterogeneous networks (HetNets). The user equipment (UEs) in the network are modeled as rational agents that engage in a non-cooperative game where each UE allocates its available transmit power over the set of assigned subcarriers so as to maximize its individual utility (defined as the user's throughput per Watt of transmit power) subject to minimum-rate constraints. In this framework, the relevant solution concept is that of Debreu equilibrium, a generalization of Nash equilibrium which accounts for the case where an agent's set of possible actions depends on the actions of its opponents. Since the problem at hand might not be feasible, Debreu equilibria do not always exist. However, using techniques from fractional programming, we provide a characterization of equilibrial power allocation profiles when they do exist. In particular, Debreu equilibria are found to be the fixed points of a water-filling best response operator whose water level is a function of minimum rate constraints and circuit power. Moreover, we also describe a set of sufficient conditions for the existence and uniqueness of Debreu equilibria exploiting the contraction properties of the best response operator. This analysis provides the necessary tools to derive a power allocation scheme that steers the network to equilibrium in an iterative and distributed manner without the need for any centralized processing. Numerical simulations are then used to validate the analysis and assess the performance of the proposed algorithm as a function of the system parameters.Comment: 37 pages, 12 figures, to appear IEEE Trans. Wireless Commu

Resource Allocation for Broadband Wireless Access Networks with Imperfect CSI

The high deployment and maintenance costs of last mile wireline networks (i.e., DSL and cable networks) have urged service providers to search for new cost-effective solutions to provide broadband connectivity. Broadband wireless access (BWA) networks, which offer a wide coverage area and high transmission rates in addition to their fast and low-cost deployment, have emerged as an alternative to last mile wireline networks. Therefore, BWA networks are expected to be deployed in areas with different terrain profiles (e.g., urban, suburban, rural) where wireless communication faces different channel impairments. This fact necessitates the adoption of various transmission technologies that combat the channel impairments of each profile. Implementation scenarios of BWA networks considered in this thesis are multicarrier-based direct transmission and single carrier-based cooperative transmission scenarios. The performance of these transmission technologies highly depends on how resources are allocated. In this thesis, we focus on the development of practical resource allocation schemes for the mentioned BWA networks implementation scenarios. In order to develop practical schemes, the imperfection of channel state information (CSI) and computational power limitations are among considered practical implementation issues. The design of efficient resource allocation schemes at the MAC layer heavily relies on the CSI reported from the PHY layer as a measure of the wireless channel condition. The channel estimation error and feedback delay renders the reported CSI erroneous. The inaccuracy in CSI propagates to higher layers, resulting in performance degradation. Although this effect is intuitive, a quantitative measure of this degradation is necessary for the design of practical resource allocation schemes. An approach to the evaluation of the ergodic mutual information that reflects this degradation is developed for single carrier, multicarrier, direct, and cooperative scenarios with inaccurate CSI. Given the CSI estimates and estimation error statistics, the presented evaluation of ergodic mutual information can be used in resource allocation and in assessing the severity of estimation error on performance degradation. A point-to-multipoint (PMP) network that employs orthogonal frequency division multiple access (OFDMA) is considered as one of the most common implementation scenarios of BWA networks. Replacing wireline networks requires not only providing the last mile connectivity to subscribers but also supporting their diverse services with stringent quality of service (QoS) requirements. Therefore, the resource allocation problem (i.e., subcarriers, rate and power allocation) is modeled as a network utility maximization (NUM) one that captures the characteristics of this implementation scenario. A dual decomposition-based resource allocation scheme that takes into consideration the diversity of service requirements and inaccuracy of the CSI estimation is developed. Numerical evaluations and simulations are conducted to validate our theoretical claims that the scheme maximizes resource utilization, coordinates with the call admission controller to guarantee QoS, and accounts for CSI inaccuracy. Cooperation has recently received great attention from the research community and industry because of its low cost and fast deployment in addition to the performance improvement it brings to BWA networks. In cooperative scenarios, subscribers cooperate to relay each other's signals. For this implementation scenario of BWA networks, a robust and constrained Kalman filter-based power allocation scheme is proposed to minimize power consumption and guarantee bit error probability (BEP) requirements. The proposed scheme is robust to CSI inaccuracy, responsive to changes in BEP requirements, and optimal in allocating resources. In summary, research results presented in this thesis contribute to the development of practical resource allocation schemes for BWA networks

QoS-aware Adaptive Resource Management in OFDMA Networks

PhDOne important feature of the future communication network is that users in the network are required to experience a guaranteed high quality of service (QoS) due to the popularity of multimedia applications. This thesis studies QoS-aware radio resource management schemes in different OFDMA network scenarios. Motivated by the fact that in current 4G networks, the QoS provisioning is severely constrained by the availability of radio resources, especially the scarce spectrum as well as the unbalanced traffic distribution from cell to cell, a joint antenna and subcarrier management scheme is proposed to maximise user satisfaction with load balancing. Antenna pattern update mechanism is further investigated with moving users. Combining network densi fication with cloud computing technologies, cloud radio access network (C-RAN) has been proposed as the emerging 5G network architecture consisting of baseband unit (BBU) pool, remote radio heads (RRHs) and fronthaul links. With cloud based information sharing through the BBU pool, a joint resource block and power allocation scheme is proposed to maximise the number of satisfi ed users whose required QoS is achieved. In this scenario, users are served by high power nodes only. With spatial reuse of system bandwidth by network densi fication, users' QoS provisioning can be ensured but it introduces energy and operating effciency issue. Therefore two network energy optimisation schemes with QoS guarantee are further studied for C-RANs: an energy-effective network deployment scheme is designed for C-RAN based small cells; a joint RRH selection and user association scheme is investigated in heterogeneous C-RAN. Thorough theoretical analysis is conducted in the development of all proposed algorithms, and the effectiveness of all proposed algorithms is validated via comprehensive simulations.China Scholarship Counci