961 research outputs found
Energy-Efficient Heterogeneous Cellular Networks with Spectrum Underlay and Overlay Access
In this paper, we provide joint subcarrier assignment and power allocation
schemes for quality-of-service (QoS)-constrained energy-efficiency (EE)
optimization in the downlink of an orthogonal frequency division multiple
access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering
underlay transmission, where spectrum-efficiency (SE) is fully exploited, the
EE solution involves tackling a complex mixed-combinatorial and non-convex
optimization problem. With appropriate decomposition of the original problem
and leveraging on the quasi-concavity of the EE function, we propose a
dual-layer resource allocation approach and provide a complete solution using
difference-of-two-concave-functions approximation, successive convex
approximation, and gradient-search methods. On the other hand, the inherent
inter-tier interference from spectrum underlay access may degrade EE
particularly under dense small-cell deployment and large bandwidth utilization.
We therefore develop a novel resource allocation approach based on the concepts
of spectrum overlay access and resource efficiency (RE) (normalized EE-SE
trade-off). Specifically, the optimization procedure is separated in this case
such that the macro-cell optimal RE and corresponding bandwidth is first
determined, then the EE of small-cells utilizing the remaining spectrum is
maximized. Simulation results confirm the theoretical findings and demonstrate
that the proposed resource allocation schemes can approach the optimal EE with
each strategy being superior under certain system settings
Energy-Efficient Scheduling and Power Allocation in Downlink OFDMA Networks with Base Station Coordination
This paper addresses the problem of energy-efficient resource allocation in
the downlink of a cellular OFDMA system. Three definitions of the energy
efficiency are considered for system design, accounting for both the radiated
and the circuit power. User scheduling and power allocation are optimized
across a cluster of coordinated base stations with a constraint on the maximum
transmit power (either per subcarrier or per base station). The asymptotic
noise-limited regime is discussed as a special case. %The performance of both
an isolated and a non-isolated cluster of coordinated base stations is examined
in the numerical experiments. Results show that the maximization of the energy
efficiency is approximately equivalent to the maximization of the spectral
efficiency for small values of the maximum transmit power, while there is a
wide range of values of the maximum transmit power for which a moderate
reduction of the data rate provides a large saving in terms of dissipated
energy. Also, the performance gap among the considered resource allocation
strategies reduces as the out-of-cluster interference increases.Comment: to appear on IEEE Transactions on Wireless Communication
A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning
In this tutorial paper, a comprehensive survey is given on several major
systematic approaches in dealing with delay-aware control problems, namely the
equivalent rate constraint approach, the Lyapunov stability drift approach and
the approximate Markov Decision Process (MDP) approach using stochastic
learning. These approaches essentially embrace most of the existing literature
regarding delay-aware resource control in wireless systems. They have their
relative pros and cons in terms of performance, complexity and implementation
issues. For each of the approaches, the problem setup, the general solution and
the design methodology are discussed. Applications of these approaches to
delay-aware resource allocation are illustrated with examples in single-hop
wireless networks. Furthermore, recent results regarding delay-aware multi-hop
routing designs in general multi-hop networks are elaborated. Finally, the
delay performance of the various approaches are compared through simulations
using an example of the uplink OFDMA systems.Comment: 58 pages, 8 figures; IEEE Transactions on Information Theory, 201
Radio resource allocation for uplink OFDMA systems with finite symbol alphabet inputs
In this paper, we consider the radio resource allocation problem for uplink orthogonal frequency-division multiple-access (OFDMA) systems. The existing algorithms have been derived under the assumption of Gaussian inputs due to its closed-form expression of mutual information. For the sake of practicality, we consider the system with finite symbol alphabet (FSA) inputs and solve the problem by capitalizing on the recently revealed relationship between mutual information and minimum mean square error (MMSE). We first relax the problem to formulate it as a convex optimization problem, and then, we derive the optimal solution via decomposition methods. The optimal solution serves as an upper bound on the system performance. Due to the complexity of the optimal solution, a low-complexity suboptimal algorithm is proposed. Numerical results show that the presented suboptimal algorithm can achieve performance very close to the optimal solution and that it outperforms the existing suboptimal algorithms. Furthermore, using our proposed algorithm, significant power saving can be achieved in comparison to the case when a Gaussian input is assumed
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 Heterogeneous Cellular Networks with Spectrum Underlay and Overlay Access
IEEE In this paper, we provide joint subcarrier assignment and power allocation schemes for quality-of-service (QoS)-constrained energy-efficiency (EE) optimization in the downlink of an orthogonal frequency division multiple access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering underlay transmission, where spectrum-efficiency (SE) is fully exploited, the EE solution involves tackling a complex mixed-combinatorial and non-convex optimization problem. With appropriate decomposition of the original problem and leveraging on the quasi-concavity of the EE function, we propose a dual-layer resource allocation approach and provide a complete solution using difference-of-two-concave-functions approximation, successive convex approximation and gradient-search method. On the other hand, the inherent inter-tier interference from spectrum underlay access may degrade EE particularly under dense small-cell deployment and large bandwidth utilization. We therefore develop a novel resource allocation approach based on the concepts of spectrum overlay access and resource efficiency (RE) (normalized EE-SE trade-off). Specifically, the optimization procedure is separated where the macro-cell optimal RE and the corresponding bandwidth is first determined, then the EE of small-cells utilizing the remaining spectrum is maximized. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation schemes can approach the optimal EE with each strategy being superior under certain system settings
Resource Allocation for Outdoor-to-Indoor Multicarrier Transmission with Shared UE-side Distributed Antenna Systems
In this paper, we study the resource allocation algorithm design for downlink
multicarrier transmission with a shared user equipment (UE)-side distributed
antenna system (SUDAS) which utilizes both licensed and unlicensed frequency
bands for improving the system throughput. The joint UE selection and
transceiver processing matrix design is formulated as a non-convex optimization
problem for the maximization of the end-to-end system throughput (bits/s). In
order to obtain a tractable resource allocation algorithm, we first show that
the optimal transmitter precoding and receiver post-processing matrices jointly
diagonalize the end-to-end communication channel. Subsequently, the
optimization problem is converted to a scalar optimization problem for multiple
parallel channels, which is solved by using an asymptotically optimal iterative
algorithm. Simulation results illustrate that the proposed resource allocation
algorithm for the SUDAS achieves an excellent system performance and provides a
spatial multiplexing gain for single-antenna UEs.Comment: accepted for publication at the IEEE Vehicular Technology Conference
(VTC) Spring, Glasgow, Scotland, UK, May 201
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