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-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

Flexible resource allocation for joint optimization of energy and spectral efficiency in OFDMA multi-cell networks

The radio resource allocation problem is studied, aiming to jointly optimize the energy efficiency (EE) and spectral efficiency (SE) of downlink OFDMA multi-cell networks. Different from existing works on either EE or SE optimization, a novel EE-SE tradeoff (EST) metric, which can capture both the EST relation and the individual cells’ preferences for EE or SE performance, is introduced as the utility function for each base station (BS). Then the joint EE-SE optimization problem is formulated, and an iterative subchannel allocation and power allocation algorithm is proposed. Numerical results show that the proposed algorithm can exploit the EST relation flexibly and optimize the EE and SE simultaneously to meet diverse EE and SE preferences of individual cells.<br/

Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM Systems

Most existing work on adaptive allocation of subcarriers and power in multiuser orthogonal frequency division multiplexing (OFDM) systems has focused on homogeneous traffic consisting solely of either delay-constrained data (guaranteed service) or non-delay-constrained data (best-effort service). In this paper, we investigate the resource allocation problem in a heterogeneous multiuser OFDM system with both delay-constrained (DC) and non-delay-constrained (NDC) traffic. The objective is to maximize the sum-rate of all the users with NDC traffic while maintaining guaranteed rates for the users with DC traffic under a total transmit power constraint. Through our analysis we show that the optimal power allocation over subcarriers follows a multi-level water-filling principle; moreover, the valid candidates competing for each subcarrier include only one NDC user but all DC users. By converting this combinatorial problem with exponential complexity into a convex problem or showing that it can be solved in the dual domain, efficient iterative algorithms are proposed to find the optimal solutions. To further reduce the computational cost, a low-complexity suboptimal algorithm is also developed. Numerical studies are conducted to evaluate the performance the proposed algorithms in terms of service outage probability, achievable transmission rate pairs for DC and NDC traffic, and multiuser diversity.Comment: 29 pages, 8 figures, submitted to IEEE Transactions on Wireless Communication

Green OFDMA Resource Allocation in Cache-Enabled CRAN

Cloud radio access network (CRAN), in which remote radio heads (RRHs) are deployed to serve users in a target area, and connected to a central processor (CP) via limited-capacity links termed the fronthaul, is a promising candidate for the next-generation wireless communication systems. Due to the content-centric nature of future wireless communications, it is desirable to cache popular contents beforehand at the RRHs, to reduce the burden on the fronthaul and achieve energy saving through cooperative transmission. This motivates our study in this paper on the energy efficient transmission in an orthogonal frequency division multiple access (OFDMA)-based CRAN with multiple RRHs and users, where the RRHs can prefetch popular contents. We consider a joint optimization of the user-SC assignment, RRH selection and transmit power allocation over all the SCs to minimize the total transmit power of the RRHs, subject to the RRHs' individual fronthaul capacity constraints and the users' minimum rate constraints, while taking into account the caching status at the RRHs. Although the problem is non-convex, we propose a Lagrange duality based solution, which can be efficiently computed with good accuracy. We compare the minimum transmit power required by the proposed algorithm with different caching strategies against the case without caching by simulations, which show the significant energy saving with caching.Comment: Presented in IEEE Online Conference on Green Communications (Online GreenComm), Nov. 2016 (Invited Paper