Energy-Efficient Power Control for Contention-Based Synchronization in OFDMA Systems with Discrete Powers and Limited Feedback

This work derives a distributed and iterative algorithm by which mobile terminals can selfishly control their transmit powers during the synchronization procedure specified by the IEEE 802.16m and the 3GPP-LTE standards for orthogonal frequency-division multiple-access technologies. The proposed solution aims at maximizing the energy efficiency of the network and is derived on the basis of a finite noncooperative game in which the players have discrete action sets of transmit powers. The set of Nash equilibria of the game is investigated, and a distributed power control algorithm is proposed to achieve synchronization in an energy-efficient manner under the assumption that the feedback from the base station is limited. Numerical results show that the proposed solution improves the energy efficiency as well as the timing estimation accuracy of the network compared to existing alternatives, while requiring a reasonable amount of information to be exchanged on the return channel

Energy efficient power control for device to device communication in 5G networks

Next generation cellular networks require high capacity, enhanced energy efficiency and guaranteed quality of service (QoS). In order to meet these targets, device-to device (D2D) communication is being considered for future 5th generation especially for certain applications that require the proximity gain, the reuse gain, and the hop gain. In this paper, we investigate energy efficient power control for the uplink of an OFDMA (orthogonal frequency-division multiple access) single-cell communication system composed of both regular cellular users and device to device (D2D) pairs. Firstly, we analyze and mathematically model the actual requirements forD2D communications and traditional cellular links in terms of minimum rate and maximum power requirement. Secondly, we use fractional programming in order to transform the original problem into an equivalent concave one and we use the non-cooperative Game theory in order to characterize the equilibrium. Then, the solution of the game is given as a water-filling power allocation. Furthermore, we implement a distributed power allocation scheme using three ways: a) Fractional programming techniques b) Closed form expression (the novelty is the use of wright omega function). c) Inverse water filling. Finally, simulations in both static and dynamic channel setting are presented to illustrate the improved performance in term of EE, SE (spectral efficiency) and time of execution of the iterative algorithm (Dinkelbach) than the closed form algorithms

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

Interference Coordination via Power Domain Channel Estimation

A novel technique is proposed which enables each transmitter to acquire global channel state information (CSI) from the sole knowledge of individual received signal power measurements, which makes dedicated feedback or inter-transmitter signaling channels unnecessary. To make this possible, we resort to a completely new technique whose key idea is to exploit the transmit power levels as symbols to embed information and the observed interference as a communication channel the transmitters can use to exchange coordination information. Although the used technique allows any kind of {low-rate} information to be exchanged among the transmitters, the focus here is to exchange local CSI. The proposed procedure also comprises a phase which allows local CSI to be estimated. Once an estimate of global CSI is acquired by the transmitters, it can be used to optimize any utility function which depends on it. While algorithms which use the same type of measurements such as the iterative water-filling algorithm (IWFA) implement the sequential best-response dynamics (BRD) applied to individual utilities, here, thanks to the availability of global CSI, the BRD can be applied to the sum-utility. Extensive numerical results show that significant gains can be obtained and, this, by requiring no additional online signaling

Electromagnetic Emission-Aware Scheduling for the Uplink of Multicell OFDM Wireless Systems

The increasing demand for data and multimedia services, as well as the ubiquitous nature of the current generation of mobile devices have resulted in continuous network upgrades to support an ever-increasing number of users. Given that wireless communication systems rely on radiofrequency waves, the electromagnetic (EM) emissions from these systems are increasingly becoming a concern, especially in terms of adverse health effects. In order to address these concerns, we propose a novel resource allocation scheme for minimizing the EM emission of users in the uplink of multicell OFDM systems, while ensuring quality of service. Our scheme is based on the assumption that long-term channel state information of all the users in the network is available. A new multicell user grouping that uses the received interference powers of the users of different sectors is proposed. Furthermore, we propose two power allocation algorithms to minimize EM emission. The first power allocation algorithm performs multicell iterative optimization to obtain the transmit powers of each user in the system. On the other hand, our second power allocation algorithm uses the average channel gains of the users of different sectors to obtain an approximation of the transmit power of each user without multicell iterative optimization. As a result, this approach has a reduced complexity when compared to our first power allocation algorithm. Simulation results show that our scheme reduces EM emission by up to 70% when compared to a single cell EM emission aware scheme and by over 3 to 4 orders of magnitude when compared to spectral efficiency maximization schemes