A Survey of Network Optimization Techniques for Traffic Engineering

TCP/IP represents the reference standard for the implementation of interoperable communication networks. Nevertheless, the layering principle at the basis of interoperability severely limits the performance of data communication networks, thus requiring proper configuration and management in order to provide effective management of traffic flows. This paper presents a brief survey related to network optimization using Traffic Engineering algorithms, aiming at providing additional insight to the different alternatives available in the scientific literature

Physical Layer Service Integration in 5G: Potentials and Challenges

High transmission rate and secure communication have been identified as the key targets that need to be effectively addressed by fifth generation (5G) wireless systems. In this context, the concept of physical-layer security becomes attractive, as it can establish perfect security using only the characteristics of wireless medium. Nonetheless, to further increase the spectral efficiency, an emerging concept, termed physical-layer service integration (PHY-SI), has been recognized as an effective means. Its basic idea is to combine multiple coexisting services, i.e., multicast/broadcast service and confidential service, into one integral service for one-time transmission at the transmitter side. This article first provides a tutorial on typical PHY-SI models. Furthermore, we propose some state-of-the-art solutions to improve the overall performance of PHY-SI in certain important communication scenarios. In particular, we highlight the extension of several concepts borrowed from conventional single-service communications, such as artificial noise (AN), eigenmode transmission etc., to the scenario of PHY-SI. These techniques are shown to be effective in the design of reliable and robust PHY-SI schemes. Finally, several potential research directions are identified for future work.Comment: 12 pages, 7 figure

Spectral Efficiency of Multi-User Adaptive Cognitive Radio Networks

In this correspondence, the comprehensive problem of joint power, rate, and subcarrier allocation have been investigated for enhancing the spectral efficiency of multi-user orthogonal frequency-division multiple access (OFDMA) cognitive radio (CR) networks subject to satisfying total average transmission power and aggregate interference constraints. We propose novel optimal radio resource allocation (RRA) algorithms under different scenarios with deterministic and probabilistic interference violation limits based on a perfect and imperfect availability of cross-link channel state information (CSI). In particular, we propose a probabilistic approach to mitigate the total imposed interference on the primary service under imperfect cross-link CSI. A closed-form mathematical formulation of the cumulative density function (cdf) for the received signal-to-interference-plus-noise ratio (SINR) is formulated to evaluate the resultant average spectral efficiency (ASE). Dual decomposition is utilized to obtain sub-optimal solutions for the non-convex optimization problems. Through simulation results, we investigate the achievable performance and the impact of parameters uncertainty on the overall system performance. Furthermore, we present that the developed RRA algorithms can considerably improve the cognitive performance whilst abide the imposed power constraints. In particular, the performance under imperfect cross-link CSI knowledge for the proposed `probabilistic case' is compared to the conventional scenarios to show the potential gain in employing this scheme

Channel Assignment Method for Maximizing Throughput in the Internet of Things System

The growth of the number of interconnected wireless devices such as the Internet of Things (IoT) is continuously increasing across various sectors, including smart buildings, smart offices, smart cities, and others. According to estimates, by the year 2030, there will be at least 50 billion devices interconnected through networks. The escalating number of uncontrolled wireless devices can lead to various issues such as interference, collisions, and data loss, resulting in an overall decline in network system performance. This study aims to propose a scenario as an alternative solution to optimize the overall network performance in the system by assigning channels to each interconnected wireless pair to reduce the impact of interference. This research indicates that the proposed method successfully enhances the system throughput performance by 39.75% compared to the condition where all wireless pairs operate on the same channel, thereby outperforming several other comparative methods.The growth in the number of wireless devices, such as the Internet of Things (IoT), interconnectedly continues to rise across various sectors like smart buildings, smart cities, and others. It is estimated that by 2030, at least 50 billion devices will be interconnected through networks. The escalating number of uncontrollable wireless devices can lead to various issues such as interference, collisions, and data loss, resulting in an overall system performance decline. This research aims to propose scenarios as an alternative solution to optimize the overall network performance through channel assignment for each interconnected wireless pair, reducing the impact of interference through a computational approach. Minimizing this impact will directly enhance the overall system throughput performance. The research results demonstrate that the proposed scenarios successfully improved the system throughput performance by 39.75% compared to the condition where all wireless pairs operate on the same channel, surpassing several other comparative algorithms