Spectrum In Wireless Networks Research Articles

Multiple Access Control in a Centralized Full-Duplex Cognitive Machine Type Network with RF Energy Harvesting

Machine type communication connecting machines in the Internet of Things (IoT) brings massive traffic and rapidly increases the demand for radio spectrum in wireless networks. To transmit the traffic in limited spectra, a time division multiple access (TDMA) based interface with a reservation scheme, which is spectrum-efficient, energy-efficient, and deployment-economical, was proposed in cognitive radio based machine type communication. Since radio frequency (RF) energy harvesting is a way to charge stand-alone or low-power machines in IoT and full-duplex communication potentially doubles spectral efficiency, this paper proposes a multiple access control that incorporates RF energy harvesting and full-duplex communication into the TDMA based interface with a reservation scheme. The proposed multiple access control elaborately uses the full-duplex functionality with a mechanism of detecting primary users to appropriately turn on/off RF charging such that the trade-off between the interference of primary users and RF charging is balanced. Extensive simulation results show that the proposed multiple access control produces high system throughput while the interference of primary users is kept at a low level.

Study on Spectrum Allocation and Optimization of Wireless Communication Networks Based on SFOA

Wireless communication network spectrum is a limited resource. With the rapid increase of mobile communication services in recent years, traditional spectrum allocation methods are only based on a fixed spectrum allocation strategy, which often results in uneven and wasteful resource allocation. Therefore, spectrum allocation and the optimization problem need to be solved urgently. The application of semantic mobile computing in the Internet of Things and the research of emerging bionic models provide new ideas for this problem. In order to solve the problem of spectrum optimization and allocation, this paper proposes an optimization algorithm that simulates fisherman fishing to reasonably arrange the allocation and optimization of wireless network spectrum. This paper selects SFOA and the other two algorithms, designs experimental functions to perform calculations separately, obtains relevant data indicators, and uses comparative analysis to analyze. The analysis shows that in terms of performance, the success rate of SFOA is higher than that of PSO, and the success rate of the two function calculations has reached 100%. In the signal‐to‐noise ratio analysis, when the signal‐to‐noise ratio is ‐4 dB, the throughput of GPSO reaches the maximum value of 0.17, the throughput of PSO reaches the maximum value of 0.56, and the throughput of SFOA reaches 1, which shows that SFOA is adopted. The stability and accuracy of the algorithm are higher than the other two algorithms, and in the case of high signal‐to‐noise ratio, the advantages of the SFOA algorithm are also more obvious. This shows that the use of this algorithm will be very helpful for spectrum allocation and optimization. Because SFOA has high stability and accuracy, through reasonable adjustment and improvement, it can make good use of spectrum allocation and optimization. Chinese wireless communication network and the development of Internet of Things technology are of great significance.

Analysis of Spectrum Selection Methods Based on Platform-Qualnet in Cognitive Radio Networks

Dynamic spectrum Access （DSA）is used to make use of the spectrum in wireless network. In most situations, control channel is a common approach to negotiation between secondary users. But, based on this feature, the attacker can destroy the communication network only influence the control center. So, in this paper, two methods without control channel are simulated in Qualent platform. The results prove that those methods are available, and the Receiver-directed channel selection is more match to the regular control channel standards in throughput.

Utilization of Millimeter‐Wave Spectrum in Wireless Networks

Utilization of Millimeter‐Wave Spectrum in Wireless Networks

Freenet: Spectrum and energy harvesting wireless networks

The dramatic growth in mobile data traffic is resulting in spectrum crunch, and is also leading to exorbitant energy consumption. Thus, it is desirable to liberate mobile and wireless networks from the constraint of spectrum scarcity and to rein in growing energy consumption. This article introduces FreeNet, figuratively synonymous with “Free Network,” which engineers spectrum and energy harvesting techniques to alleviate spectrum and energy constraints by sensing and harvesting spare spectrum for data communications and utilizing renewable energy as power supplies, respectively. Hence, FreeNet increases the spectrum and energy efficiency of wireless networks and enhances network availability. As a result, FreeNet can be deployed to alleviate network congestion in urban areas, provision broadband services in rural areas, and upgrade emergency communication capacity. This article provides a brief analysis of the design of FreeNet that accommodates the dynamics of the spare spectrum and employs renewable energy.

Distributed Interference-Aware Cooperative MAC Based on Stackelberg Pricing Game

Cooperative communication can significantly enhance the efficient utilization of spectrum in wireless networks. The performance of wireless cooperative networks depends on careful medium access control (MAC) and resource allocation such as relay selection and cooperative link scheduling policy for interference management. Most of the previous centralized works rely on precise instantaneous channel state information (CSI). In this paper, considering the impact of multirelay link interference on relay selection and dynamic spectrum sharing, we propose a fully distributed relay MAC scheme for wireless cooperative networks based on a Stackelberg game framework with only one-hop local CSI, where source nodes that have their own information to send act as leader users and where the others act as follower users. In this scenario, each relay node prices its spectrum resource to the corresponding source node to maximize its revenue. In addition, the proposed scheme helps not only source nodes to find relay nodes by channel gains and obtain an optimal system performance but relay nodes to maximize their revenue by asking a suitable resource price as well. The interactions between the sources and relays iteratively lead to a Stackelberg equilibrium, in which the cooperation system achieves high throughput and low transmission delay. Simulation results are presented to show the effectiveness of the proposed approach.

Co-Operation Based Resource Selection in Cognitive Radio Network via Potential Games

Cognitive Radio is a forthcoming technique to improvise the utilization of radio frequency spectrum in wireless network. However, Cognitive Radio Network has several challenges such as channel selection, efficient spectrum sharing, network throughput, etc. This paper presents a resource (channel) selection strategy by the Secondary Users (SUs) in a dynamic environment via game theoretic approach namely potential games. A distributed, Stochastic Learning based Resource Selection (SLRS) and Q-Learning based Resource Selection (QLRS) are the two different algorithms proposed here. The strategy followed by the SU is based on its own action-reward history, even without knowing the actions in other SUs. The simulation results prove that the QLRS algorithm achieves higher throughput and fairness performances than the SLRS algorithm.

CogNS: A Simulation Framework for Cognitive Radio Networks

Cognitive radio technology has been used to efficiently utilize the spectrum in wireless networks. Although many research studies have been done recently in the area of cognitive radio networks (CRNs), little effort has been made to propose a simulation framework for CRNs. In this paper, a simulation framework based on NS2 (CogNS) for cognitive radio networks is proposed. This framework can be used to investigate and evaluate the impact of lower layers, i.e., MAC and physical layer, on the transport and network layers protocols. Due to the importance of packet drop probability, end-to-end delay and throughput as QoS requirements in real-time reliable applications, these metrics are evaluated over CRNs through CogNS framework. Our simulations demonstrate that the design of new network and transport layer protocols over CRNs should be considered based on CR-related parameters such as activity model of primary users, sensing time and frequency.

Competitive spectrum sharing in cognitive radio networks: a dynamic game approach

Cognitive is an emerging technique to improve the utilization of radio frequency spectrum in wireless networks. In this paper, we consider the problem of spectrum sharing among a primary user and multiple secondary users. We formulate this problem as an oligopoly market competition and use a noncooperative game to obtain the spectrum allocation for secondary users. Nash equilibrium is considered as the solution of this game. We first present the formulation of a static game for the case where all secondary users have the current information of the adopted strategies and the payoff of each other. However, this assumption may not be realistic in some cognitive radio systems. Therefore, we consider the case of bounded rationality in which the secondary users gradually and iteratively adjust their strategies based on the observations on their previous strategies. The speed of adjustment of the strategies is controlled by the learning rate. The stability condition of the dynamic behavior for this spectrum sharing scheme is investigated. The numerical results reveal the dynamics of distributed dynamic adaptation of spectrum sharing strategies.

Formula omitted] labeling of d-dimensional grids

In this paper, we address the problem of λ labelings, that was introduced in the context of frequency assignment for telecommunication networks. In this model, stations within a given radius r must use frequencies that differ at least by a value p, while stations that are within a larger radius r ′ > r must use frequencies that differ by at least another value q. The aim is to minimize the span of frequencies used in the network. This can be modeled by a graph coloring problem, called the L ( p , q ) labeling, where one wants to label vertices of the graph G modeling the network by integers in the range [ 0 ; M ] , in such a way that: (1) neighbors in G are assigned colors differing by at least p and (2) vertices at distance 2 in G are assigned colors differing by at least q, while minimizing the value of M. M is then called the λ number of G, and is denoted by λ q p ( G ) . In this paper, we study the L ( p , q ) labeling for a specific class of networks, namely the d-dimensional grid G d = G [ n 1 , n 2 , … , n d ] . We give bounds on the value of the λ number of an L ( p , q ) labeling for any d ⩾ 1 and p , q ⩾ 0 . Some of these results are optimal (namely, in the following cases: (1) p = 0 , (2) q = 0 , (3) q = 1 (4) p , q ⩾ 1 , p = α · q with 1 ⩽ α ⩽ 2 d and (5) p ⩾ 2 dq + 1 ); when the results we obtain are not optimal, we observe that the bounds differ by an additive factor never exceeding 2 q - 2 . The optimal result we obtain in the case q = 1 answers an open problem stated by Dubhashi et al. [Channel assignment for wireless networks modelled as d -dimensional square grids, in: Proceedings of the IWDC’02, International Workshop on Distributed Computing, Lecture Notes in Computer Science, vol. 2571, Springer, Berlin, 2002, pp. 130–141], and generalizes results from [A.A Bertossi, C.M. Pinotti, R.B. Tan, Efficient use of radio spectrum in wireless networks with channel separation between close stations, in: Proceedings of the DIAL M for Mobility 2000, Fourth International Workshop on Discrete Algorithms and Methods for Mobile Computing and communications, 2000; A. Dubhashi, S. MVS, A. Pati, S. R., A.M. Shende, Channel assignment for wireless networks modelled as d -dimensional square grids, in: Proceedings of the IWDC’02, International Workshop on Distributed Computing, Lecture Notes in Computer Science, vol. 2571, Springer, Berlin, 2002, pp. 130–141]. We also apply our results to get upper bounds for the L ( p , q ) labeling of d-dimensional hypercubes.