An Adaptive Transmission Mode Selection Scheme for Cellular Underlaid D2D Communication

In this paper, we propose to use Artificial Bee Colony (ABC) optimization to solve the joint mode selection, channel assignment, and power allocation (JMSCPA) problem to maximize system throughput and spectral efficiency. JMSCPA is a problem where the allocation of channel and power depends on the mode selection. Such problems require two step solution and are called bi-level optimization problems. As bi-level optimization increases the complexity and computational time, we propose a modified version of single-level ABC algorithm aided with the adaptive transmission mode selection algorithm to allocate the cellular, reuse, and dedicated modes to the DUs along with channel and power allocation based on the network traffic load scenarios. A single variable, represented by the users (CUs and DUs) is used to allocate mode selection, and channel allocation to solve the JMSCPA problem, leading to a simpler solution with faster convergence, and significant reduction in the computational complexity which scales linearly with the number of users. Further, the proposed solution avoids premature stagnation of conventional ABC into local minima by incorporating a modification in its update procedure. The efficacy of the ABC-aided approach, as compared to the results reported in the literature, is validated by extensive numerical investigations under different simulation scenarios.

     

Direct conversion receiver for radio communication systems

Direct conversion receiver (DCR) architecture, which has introduced the zero intermediate frequency (IF) approach, supports efficient wireless handset designs with a high level of integration. Transmission over wireless channels is subject to time dispersion due to multipath propagation and frequency dispersion due to Doppler effect, the design of wireless receivers are tremendously important in supporting reliable communication links. With wireless technology growing, the choice of optimal wireless receiver architecture that supports monolithic integration without performance degradation becomes an important dimension in modern handset design. The increasing demand for mobile terminals with smaller physical dimensions has led to the investigation of DCR, which supports single chip and multinode designs. Since DCR is a promising architecture for fourth generation mobile terminals, it is important to note that implementation of a certain dc offset technique does not compromise the benefits of low complexity receiver design.     

An energy‐efficient utility‐based distributed data routing scheme for heterogenous sensor networks

A utility‐based distributed data routing algorithm is proposed and evaluated for heterogeneous wireless sensor networks. It is energy efficient and is based on a game‐theoretic heuristic load‐balancing approach. It runs on a hierarchical graph arranged as a tree with parents and children. Sensor nodes are considered heterogeneous in terms of their generated traffic, residual energy and data transmission rate and the bandwidth they provide to their children for communication. The proposed method generates a data routing tree in which child nodes are joined to parent nodes in an energy‐efficient way. The principles of the Stackelberg game, in which parents as leaders and children as followers, are used to support the distributive nature of sensor networks. In this context, parents behave cooperatively and help other parents to adjust their loads, while children act selfishly. Simulation results indicate the proposed method can produce on average more load‐balanced trees, resulting in over 30% longer network lifetime compared with the cumulative algorithm proposed in the literature. Copyright © 2014 John Wiley & Sons, Ltd.     

Bee colony optimization aided adaptive resource allocation in OFDMA systems with proportional rate constraints

Orthogonal frequency division multiple access (OFDMA) is a promising technique, which can provide high downlink capacity for the emerging wireless systems. The total capacity of OFDMA can be maximized by adaptively assigning subcarriers to the users with the best gains for those subcarriers, with power subsequently distributed by water-filling. In this paper, we propose the use of artificial bee colony (ABC) algorithm combined with Deb’s selection mechanism to handle the constraints. In this scheme, a probabilistic selection scheme assigns probability values to feasible solutions based on their fitness values and to infeasible individuals based on their violations, to allocate the resources to the users in downlink OFDMA system. Specifically we propose two approaches for resource allocation in downlink OFDMA systems using ABC algorithm. In the first approach, ABC algorithm is used for subcarrier allocation only, while in second approach the ABC algorithm is used for joint subcarrier and power allocation. It is shown that both these approaches obtain higher sum capacities as compared to that obtained by previous works, with comparable computational complexity. It is also shown that the joint subcarrier and power allocation approach provides near optimal results at the cost of slightly higher computational cost.     

A unified analytical framework for distributed variable step size LMS algorithms in sensor networks

Internet of Things (IoT) is helping to create a smart world by connecting sensors in a seamless fashion. With the forthcoming fifth generation (5G) wireless communication systems, IoT is becoming increasingly important since 5G will be an important enabler for the IoT. Sensor networks for IoT are increasingly used in diverse areas, e.g., in situational and location awareness, leading to proliferation of sensors at the edge of physical world. There exist several variable step-size strategies in literature to improve the performance of diffusion-based Least Mean Square (LMS) algorithm for estimation in wireless sensor networks. However, a major drawback is the complexity in the theoretical analysis of the resultant algorithms. Researchers use several assumptions to find closed-form analytical solutions. This work presents a unified analytical framework for distributed variable step-size LMS algorithms. This analysis is then extended to the case of diffusion based wireless sensor networks for estimating a compressible system and steady state analysis is carried out. The approach is applied to several variable step-size strategies for compressible systems. Theoretical and simulation results are presented and compared with the existing algorithms to show the superiority of proposed work.     

Energy-Efficient Resource Allocation in Underlay D2D Communication using ABC Algorithm

Wireless Personal Communications - Due to the limited resources of Internet of Things (IoT) nodes, routing protocols for these networks should be designed in such a way that not only reduce the...     

Energy Cooperation with Sleep Mechanism in Renewable Energy Assisted Cellular HetNets

The emerging fifth generation (5G) and beyond radio access networks are expected to be extremely dense and heterogeneous as compared to the current networks, involving a large number of different classes of base stations (BSs), namely macro, micro, femto and pico BSs. Among several performance requirements 5G and beyond systems aim to achieve, energy efficiency is one of the crucial requirements. In order to achieve energy-efficient design in dense heterogeneous 5G networks, various approaches in terms of resource allocation, off-loading techniques, hardware solutions and energy harvesting are being considered. In this regard, this paper develops an energy usage optimization framework in a cellular heterogeneous network (HetNet) consisting of a central macro-BS and a number of micro-BSs, equipped with renewable energy sources (RESs) such as solar panels and wind turbines. The proposed framework incorporates an energy cooperation mechanism along with a sleep mechanism (BS ON/OFF switching), in which the BSs having lean traffic are put into a sleep mode and their traffic load gets shared by the central BS. The surplus harvested energy from RESs of the sleeping BSs can then be sold back to the grid. An optimization problem for maximizing the utilization of RES and minimizing the usage of the traditional sources, such as utility and generator, is formulated and this mixed integer non-linear programming problem is solved through an interior point method. The presented results for various HetNet sizes demonstrate the significant savings in the energy cost with the proposed RES-enabled HetNet sleep mechanism model over the conventional approaches.

     

Towards the fulfillment of 5G network requirements: technologies and challenges

Future 5G networks are expected to have the capabilities of providing extremely high data rates, seamless coverage, massive number of connected devices, low latency, etc., in order to support the internet of things era. The dynamic performance of 5G networks is a key feature for controlling the dense and rapidly changing communication environment. Technical issues such as limited frequency resources, interference, energy consumption, and network management are the main challenges facing 5G networks. This article presents a comprehensive study of 5G networks architecture, technologies, challenges, and possible solutions based on recent advances in technology and research.     

Mesh adaptive direct search approach for D2D resource management

Device‐to‐device (D2D) communications are being considered a way forward to achieve higher data rate targets for futuristic wireless networks. D2D introduces interference among cellular users and D2D users. A joint resource allocation (JRA) strategy in cellular network with D2D functionality can definitely enhance overall data rate. The strategy under consideration maximizes the overall data rate of cellular network besides meeting threshold of power and interference constraints. The JRA is a class of mixed integer non‐linear constraint optimization problems and is NP hard. Because of discrete nature of variables in the problem, optimal solution performs extensive search of integer variables, and problem becomes exponentially complex with the increasing number of user pairs. In this paper, mesh adaptive direct search algorithm is applied to solve the aforementioned problem. The algorithm is suitable for complex problems of combinatorial nature to solve the JRA strategy in D2D. The proposed algorithm converges to optimal solution within acceptable computational iterations. Simulation results of system capacity and interference also demonstrate the suitability of the proposed approach viz‐a‐viz other algorithms. Copyright © 2016 John Wiley & Sons, Ltd.