Energy-efficiency (EE) is critical for device-to-device (D2D) enabled cellular networks due to limited battery capacity and severe cochannel interference. In this paper, we address the EE optimization problem by adopting a stable matching approach. The NP-hard joint resource allocation problem is formulated as a one-to-one matching problem under two-sided preferences, which vary dynamically with channel states and interference levels. A game-theoretic approach is employed to analyze the interactions and correlations among user equipments (UEs), and an iterative power allocation algorithm is developed to establish mutual preferences based on nonlinear fractional programing. We then employ the Gale–Shapley algorithm to match D2D pairs with cellular UEs, which is proved to be stable and weak Pareto optimal. We provide a theoretical analysis and description for implementation details and algorithmic complexity. We also extend the algorithm to address scalability issues in large-scale networks by developing tie-breaking and preference-deletion-based matching rules. Simulation results validate the theoretical analysis and demonstrate that significant performance gains of average EE and matching satisfactions can be achieved by the proposed algorithm.

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Energy-Efficient Matching for Resource Allocation in D2D Enabled Cellular Networks

OFDMA has been selected as the multiple access scheme for state-of-the-art wireless communication systems. Efficient resource allocation in OFDMA wireless networks is essential in order to meet the quality of service requirements of emerging services. In this paper, a survey of resource allocation and scheduling schemes in OFDMA wireless networks is presented. The focus is on the uplink direction. Resource allocation is surveyed in various scenarios: centralized and distributed, instantaneous and ergodic, optimal and suboptimal, single cell and multicell, cooperative and non-cooperative, in addition to different combinations of these variants. Directions for future research are outlined.

A Survey on Uplink Resource Allocation in OFDMA Wireless Networks

Matching theory is a powerful tool to study the formation of dynamic and mutually beneficial relations among different types of rational and selfish agents. It has been widely used to develop high performance, low complexity, and decentralized protocols. In this article, a comprehensive survey of matching theory, its variants, and their significant properties appropriate for the demands of wireless communications and network engineers is provided. Recent research progress in applying matching theory to wireless communications to address major technical opportunities and challenges is presented. A novel classification of matching models from the practical perspective is provided, and the properties and structure of each model are explained. This will enable a network designer to select an appropriate matching model for a specific application in wireless communications. Finally, the application of different matching models to various emerging wireless networks is discussed.

Matching Theory: Applications in wireless communications

The explosive development of ICT (information and communication technology) industry has emerged as one of the major sources of world energy consumption. Therefore, this paper concerns about the BS (base station) energy saving issue, for most energy consumption of the communication network comes from the BSs and the core network. Particularly, we consider dynamically turning off certain BSs when the network traffic is low. Centralized and decentralized implementations are investigated. Simulations demonstrate the energy efficiency of the proposed algorithms and the tradeoff between energy saving and coverage guarantee.

Green mobile access network with dynamic base station energy saving (インターネットアーキテクチャ)

Base station (BS) deployment in cellular networks is one of the fundamental problems in network design. This paper proposes a novel method for the cell planning problem for fourth-generation (4G) cellular networks using metaheuristic algorithms. In this approach, we aim to satisfy both cell coverage and capacity constraints simultaneously by formulating an optimization problem that captures practical planning aspects. The starting point of the planning process is defined through a dimensioning exercise that captures both coverage and capacity constraints. Afterward, we implement a metaheuristic algorithm based on swarm intelligence (e.g., particle swarm optimization or the recently proposed gray-wolf optimizer) to find suboptimal BS locations that satisfy both problem constraints in the area of interest, which can be divided into several subareas with different spatial user densities. Subsequently, an iterative approach is executed to eliminate eventual redundant BSs. We also perform Monte Carlo simulations to study the performance of the proposed scheme and compute the average number of users in outage. Next, the problems of green planning with regard to temporal traffic variation and planning with location constraints due to tight limits on electromagnetic radiations are addressed, using the proposed method. Finally, in our simulation results, we apply our proposed approach for different scenarios with different subareas and user distributions and show that the desired network quality-of-service (QoS) targets are always reached, even for large-scale problems.

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Optimized LTE Cell Planning With Varying Spatial and Temporal User Densities

Recently, the demand for portable electronics and embedded systems has increased. These devices need low-power circuit designs because they depend on batteries as an energy resource. Moreover, multi-valued logic (MVL) circuits provide notable improvements over binary circuits in terms of interconnect complexity, chip area, propagation delay, and energy consumption. Therefore, this paper proposes new ternary circuits aiming to lower the power delay product (PDP) to save battery consumption. The proposed designs include new ternary gates [standard ternary inverter (STI) and ternary NAND (TNAND)] and combinational circuits [ternary decoder (TDecoder), ternary half-adder (THA), and ternary multiplier (TMUL)] using carbon nano-tube field-effect transistors (CNFETs). This paper employs the best trade-off between reducing the number of used transistors, utilizing energy-efficient transistor arrangement such as transmission gate, and applying the dual supply voltages (V
 dd
 and V
 dd
/2). The five proposed designs are compared with the latest 15 ternary circuits using the HSPICE simulator for different supply voltages, different temperatures, and different frequencies; 180 simulations are performed to prove the efficiency of the proposed designs. The results show the advantage of the proposed designs in reduction over 43% in terms of transistors' count for the ternary decoder and over 88%, 99%, 98%, 86%, and 78% in energy consumption (PDP) for the STI, TNAND, TDecoder, THA, and TMUL, respectively.

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High-Performance and Energy-Efficient CNFET-Based Designs for Ternary Logic Circuits

The emergence of resource-demanding wireless services such as mobile gaming or multimedia applications motivates the introduction of advanced paradigms for resource allocation in next-generation OFDMA-based wireless networks. In this context, while existing literature mainly focused on schemes in which the uplink and downlink resources are considered independently, this paper proposes a novel subcarrier allocation approach suitable for services that have coupled uplink/downlink (UL/DL) quality-of-service requirements. We model the proposed joint uplink/downlink subcarrier allocation problem as a two-sided stable matching game and we propose a corresponding novel resource allocation algorithm. Results show that the proposed stable matching algorithm enables an efficient joint uplink/downlink subcarrier allocation and yields notable performance gains, in terms of the average utility per user, relative to classical resource allocation schemes. The results also show that our approach leads to an improved fairness in the subcarrier allocation.

A stable matching game for joint uplink/downlink resource allocation in OFDMA wireless networks

The recent trend towards energy-efficient and environment-aware network operations has mandated the development of novel green network planning paradigms. In this context, while existing work focused on developing reactive energy reduction techniques after complete network deployment, this paper presents a proactive green radio network planning (RNP) algorithm that jointly optimizes base station (BS) locations and generates the BS on/off switching patterns based on the changing traffic conditions. Simulation results demonstrate considerable energy savings through dynamic adaptation of the number of simultaneous active BSs.

A proactive approach for LTE radio network planning with green considerations

The continuing growth in demand for better mobile experience, higher data rates and lower latencies is driving the development of the forthcoming generation of wireless systems, namely, 5G. Radio network planning (RNP) is one of the essential stages in deploying a wireless network that meets certain coverage, capacity and quality of service (QoS) requirements. While the RNP problem has been studied for existing wireless standards, the major advancements introduced in the upcoming 5G standard necessitate a reinvestigation of the problem. To this end, this paper investigates the RNP process in the context of the upcoming 5G networks. The planning process will minimize and optimize the locations of base stations (BSs) in a selected geographical area using a heuristic algorithm. Even though 5G is still being standardized, the paper will take into account some of the key aspects that would constitute the core of next generation networks such as the use of millimeter wave (mmw) carrier frequencies, and the eventual deployment of heterogeneous and dense networks. Different facets of the 5G RNP process are evaluated for various network scenarios.

Ahmad M. El-Hajj

Papers

High-Performance and Energy-Efficient CNFET-Based Designs for Ternary Logic Circuits

A stable matching game for joint uplink/downlink resource allocation in OFDMA wireless networks

A proactive approach for LTE radio network planning with green considerations

On Radio network planning for next generation 5G networks: A case study

EEG mobility artifact removal for ambulatory epileptic seizure prediction applications