Panagiotis D. Diamantoulakis

Wireless-Powered Communications With Non-Orthogonal Multiple Access

We study a wireless-powered uplink communication system with non-orthogonal multiple access (NOMA), consisting of one base station and multiple energy harvesting users. More specifically, we focus on the individual data rate optimization and fairness improvement and we show that the formulated problems can be optimally and efficiently solved by either linear programming or convex optimization. In the provided analysis, two types of decoding order strategies are considered, namely fixed decoding order and time sharing. Furthermore, we propose an efficient greedy algorithm, which is suitable for the practical implementation of the time-sharing strategy. The simulation results illustrate that the proposed scheme outperforms the baseline orthogonal multiple access scheme. More specifically, it is shown that the NOMA offers a considerable improvement in throughput, fairness, and energy efficiency. Also, the dependence among system throughput, minimum individual data rate, and harvested energy is revealed, as well as an interesting tradeoff between rates and energy efficiency. Finally, the convergence speed of the proposed greedy algorithm is evaluated, and it is shown that the required number of iterations is linear with respect to the number of users.

Optimal design of non-orthogonal multiple access with wireless power transfer

We study a wireless-powered uplink communication system with non-orthogonal multiple access (NOMA), consisting of one base station and multiple energy harvesting users. We focus on data rates optimization and fairness increase. We show that the formulated optimization problems can be optimally and efficiently solved by either linear programming methods or convex optimization, which means that the proposed scheme can be easily implemented in practical applications. Simulation results illustrate that the proposed scheme outperforms the baseline orthogonal multiple access scheme, while they reveal the dependence between sum-throughput, minimum data rate, and harvested energy.

Throughput Maximization in Multicarrier Wireless Powered Relaying Networks

Dynamic power allocation and power splitting, in a multicarrier two-hop link with a wireless powered relay, is investigated. We first formulate the corresponding optimization problem, which consists of the joint optimization -in terms of achievable rate- of, 1) the dynamic power allocation among multiple channels and, 2) the selection of the power splitting ratio between information processing and energy harvesting at the relay, when amplify-and-forward is applied. This is a non-convex optimization problem, which is mapped to a convex one and optimally solved using one-dimensional search and dual decomposition, while a suboptimal efficient iterative method is also proposed. Simulations reveal a significant increase in the throughput, when comparing the proposed approach with two alternative power allocation schemes, while they verify the effectiveness of the fast-converging iterative solution.

Carrier Aggregation for Cooperative Cognitive Radio Networks

The ever-increasing demand for mobile Internet and high-data-rate applications poses unique challenging requirements for 5G mobile networks, including spectrum limitations and massive connectivity. Cognitive radio and carrier aggregation (CA) have recently been proposed as promising technologies to overcome these challenges. In this paper, we investigate joint relay selection and optimal power allocation in an underlay cooperative cognitive radio with CA, taking into account the availability of multiple carrier components in two frequency bands, subject to outage probability requirements for primary users (PUs). The secondary user network employs relay selection, where the relay that maximizes the end-to-end sum rate is selected, assuming both decode-and-forward and amplify-and-forward relaying. The resulting optimization problems are optimally solved using convex optimization tools, i.e., dual decomposition and an efficient iterative method, allowing their application in practical implementations. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom efficiently to maximize the SU rate, while meeting the PU average outage probability constraints.

Joint Downlink/Uplink Design for Wireless Powered Networks With Interference

This paper jointly investigates the downlink/uplink of wireless powered networks (WPNs), which are exposed to the effect of the cascaded near-far problem, i.e., the asymmetric overall degradation of the users’ performance, due to different path-loss values. More specifically, assuming that the users are able to harvest energy both from interference and desired signals, higher path loss reduces the downlink rate of the far user, while it also negatively affects its uplink rate, since less energy can be harvested during downlink. Furthermore, if the far user is located at the cell edge, its performance is more severely impaired by interference, despite the potential gain due to energy harvesting from interference signals. To this end, we fairly maximize the downlink/uplink users’ rates, by utilizing corresponding priority weights. Two communication protocols are taken into account for the downlink, namely, time division multiple access and non-orthogonal multiple access (NOMA), while NOMA with time sharing is considered for the uplink. The formulated multidimensional non-convex optimization problems are transformed into the equivalent convex ones and can be solved with low complexity. Simulations results illustrate that: 1) a relatively high downlink rate can be achieved, while the required energy is simultaneously harvested by the users for the uplink and 2) dowlink NOMA is a more appropriate option with respect to the network topology, especially when a high downlink rate is desired.

Maximizing Proportional Fairness in Wireless Powered Communications

This letter investigates the fundamental tradeoff between sum rate and fairness of a wireless-powered uplink communication system, consisting of one base station (BS) and multiple energy harvesting users, which are coordinated through the harvest-then-transmit protocol. To this end, the optimal rate and time allocation, when aiming to maximize the proportional fairness, is investigated. Two well known communication protocols are considered, namely, time division multiple access (TDMA) and nonorthogonal multiple access with time-sharing (NOMA-TS). It is shown that NOMA-TS outperforms the considered benchmark scheme, which is the NOMA with fixed decoding order and adaptive power allocation, while TDMA proves to be an appropriate choice, when all the users are located in similar distances from the BS.

Game Theoretic Approach to Demand Side Management in Smart Grid with User-Dependent Acceptance Prices

Efficient demand side management through dynamic power pricing is an important application in the smart grids. However, in the absence of a detailed user consumption model, it is difficult to set an optimal power price. In this paper, we propose to efficiently capture the user consumption behavior through a user-dependent acceptance price. Each rational user will decide its own acceptance price based on its desire to get served. Then, we model the selfish interaction between operator and users as a Stackelberg game, where the operator aims to maximize its profit, while the individual users try to pay the lowest price and be served in time. After each user selfishly declares its own acceptance price, the operator sets an optimal power price, based on the user feedback and taking into account the random output of the renewable power sources. Simulation results confirm that the operator can maximize its profit and the users get served in time, while the proposed scheme leads to the optimal usage of the renewable power production.

Smart hybrid power system for base transceiver stations with real-time energy management

Reducing the power consumption of base transceiver stations (BTSs) in mobile communications networks is typically achieved through energy saving techniques, where they can also be combined with local power generators to create a hybrid power system (HPS). Such a system has reduced power consumption and operational cost, without taking the advantage of real-time energy management. In this paper, we introduce the smart HPS that can facilitate energy consumption scheduling (ECS) via an intelligent connection to the power grid. In doing so, we first develop sensor control and communication systems with an embedded smart ECS unit for the HPS. Then, we propose a real-time energy management algorithm to reduce the operational cost of BTS, according to real-time pricing and estimating demand and supply. The numerical results presented show a significant reduction in the BTS operational costs. We also develop a techno-economic and sizing analysis to describe the total cost of the smart HPS taking the real-time energy pricing into account. Since the lifetime of the operating system can be quite long, our results show that there is possibility to make a profit.

Underlay cognitive radio: What is the impact of carrier aggregation and relaying on throughput?

In this paper, we investigate joint relay selection and optimal power allocation, as a means to maximize the achievable rate of an underlay cooperative cognitive radio with carrier aggregation, taking into account the availability of multiple carrier components in two different bands and primary users (PUs) with specific average outage probability requirements. For the acquisition of the interference thresholds, which are set by the PUs on the secondary user (SU), we incorporate a minimum feedback strategy into the problem formulation, based on the minimization of the PUs outage probabilities. The resulting non-convex optimization problem is transformed into a convex one and optimally solved using dual decomposition and an efficient iterative method with closed-form power policies. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom in an efficient way which maximizes the SU throughput while the average outage probability of the PUs is kept at acceptable levels.

Trade-Offs in Wireless Powered Communications

We investigate trade-offs that are created in wireless powered communication networks. To this end, we take into account throughput maximization, energy efficiency, and fairness and we present and discuss the solution of several optimization problems, considering different scenarios for the network consistence, the adopted protocol, and the energy arrival knowledge. We show that all optimization problems can be solved using convex optimization, and, thus the provided solutions can be efficiently used in practical implementations.