Ali Mustafa

A Novel Approach for Fast Average Consensus Under Unreliable Communication in Distributed Multi Agent Networks

In this research an algorithm is proposed to find the total number of agents participating in a multi agent network. Also to achieve hasten distributed average consensus in order to consider a network with reliable and unreliable communication links. Class of algorithm is considered in which fixed initial state values are assigned to all agents in the network, with the iterations they updates their initial values by communicating with their neighboring agents within a multi agent network. Algorithm with weighted matrix satisfy the convergence condition of average consensus and accelerate the method to achieve the consensus. Usually this convergence process is relatively sluggish and take moreover numerous iterations to achieve a consensus. To overcome the above issues, a new approach is proposed in order to minimize the rate of convergence. A two step algorithm has been proposed, where in step one each agent employs a linear predictor to predict future agent values. In second step the computed values are used to proceed further by the other agents to achieve consensus in order to bypass the redundant states. In the end proposed algorithm is compared with other existing consensus frameworks to strengthen the claim regarding the proposed two step algorithm which leads to escalate the rate of convergence and reduces the number of iterations.

An Efficient Agent Scheming in Distributed Time Varying Networks

Time varying networks are a new paradigm for understanding and building distributed systems composed of various agents. Agents are autonomous systems and have two important attributes; First, they have some degree of independence in execution of their decision and deciding their next goal in order to achieve a global goal secondly, they are capable of interacting with other agents using a communication network. In this paper, an algorithm for agent counting is proposed for computing the total number of agents in a network by using graph and matrix theory. Simulation results indicates some of the control problems in distributed time varying networks and demonstrate the effectiveness of the established results for a fixed and switching topologies.

Deploying uninterrupted wireless communication networks by using Software Define Cognitive Radios (SDCR) and Time Division Duplex (TDD) transmission techniques in 5G networks

During the past two decades there has been a prodigious growth in the field of wireless communication networks in terms of voice, data and video applications. This growth has become an essential part of the life of the cellular users who use the high bandwidth internet services on their PDAs. In order to accommodate the cellular users use of Software Define Cognitive Radios (SDCR) is encouraged. This Software Define Cognitive Radios (SDCR) can handoff to an alternative wireless network in the event of non-signal coverage spots also referred as white or black spots, where the desire Receive Signal Strength Indications (RSSI) levels falls below the desire threshold levels to maintain the connectivity between the PDA and wireless communication network base station. Low Receive Signal Strength Indications (RSSI) levels results in low Signal to Noise Ratio (SNR) which simultaneously causes high Bit Error Rates (BER), high latency and high packet drops in wireless communication networks. Ideal latency limits in wireless links should be less than 1 msec for uninterruptable IP network communications; otherwise the quality of IP communications degrades dramatically. The most efficient wireless data transmission techniques suitable for high bandwidth wireless communication networks are Time Division Duplex (TDD). Latency in Time Division Duplex (TDD) is less than 1msec which is standard for the wireless links. Time Division Duplex (TDD) minimizes latency, which result in low Bit Error Rates (BER) and packet drops and high SNR levels due to good RSSI levels. Due to decrease in latency levels by Time Division Duplex (TDD) the baseband system can cope with the increased user throughput requirements to run high data rate applications. Use of Time Division Duplex (TDD) allows less battery consumption as compared to Frequency Division Duplex (FDD), as the transmitter only transmit on the required time slot. TDD is more flexible than FDD to support bursty traffic demand in wireless communication networks. Therefore in this research paper the Authors have proposed the use of Software Define Cognitive Radios (SDCR) and Time Division Duplex (TDD) wireless transmission techniques to avoid non signal coverage areas and Low RSSI levels to avoid signal degradation and low Bit Error Rates (BER) which results in packet drops.

Asynchronous Communication under Reliable and Unreliable Network Topologies in Distributed Multiagent Systems: A Robust Technique for Computing Average Consensus

Nearly all applications in multiagent systems demand precision, robustness, consistency, and rapid convergence in designing of distributed consensus algorithms. Keeping this thing in our sight, this research suggests a robust consensus protocol for distributed multiagent networks, continuing asynchronous communications, where agent’s states values are updated at diverse interval of time. This paper presents an asynchronous communication for both reliable and unreliable network topologies. The primary goal is to delineate local control inputs to attain time synchronization by processing the update information received by the agents associated in a communication topology. Additionally in order to accomplish the robust convergence, modelling of convergence analysis is conceded by commissioning the basic principles of graph and matrix theory alongside the suitable lemmas. Moreover, statistical examples presenting four diverse scenarios are provided in the end; produced results are the recognisable indicator to authenticate the robust effectiveness of the proposed algorithm. Likewise, a simulation comparison of the projected algorithm with the other existing approaches is conducted, considering different performance parameters are being carried out to support our claim.

Unreliable communication in high-performance distributed multi-agent systems: A ingenious scheme in high computing

Designing of distributed consensus algorithms featuring accuracy, robustness, reliability, and speed of convergence is in high demand for various multi-agent applications. In this research, it has been investigated to device a novel design of distributed estimation algorithm which can tackle the problem of unreliable communication among multi-agents to achieve consensus on the average value of their initial values and must be capable of computing the total number of agents in the system under dynamically changing interaction topologies. A dynamically changing network topology is considered in this research with unreliable communication links, and four different scenarios are established to be analyzed for the proposed consensus-based distributed estimation algorithm. This study established a consensus for a dynamically changing interaction topology among agents, for addition of agents in the network with dynamically switching topology at any instant in communication, for removal of agents from the network with dynamically switching topology at any instant in communication, and for a fixed topology with link failure and a reconnection with the same agent after each iteration. The proposed algorithm paces up the rate of convergence by reducing the number of iteration, along with sure convergence of the designed algorithm using the concepts of stochastic differential equation theory, control system theory, algebraic graph theory, and algebraic matrix theory. Finally, in the end, simulation results are provided which are clear evidence to validate the effectiveness of theoretical results of the proposed algorithm in comparison to previously known consensus algorithms in terms of different performance parameters.

Pairing and Scheduling for Large Array MIMO Using Regularized Channel Inversion Receivers Over Nakagami-m Fading

Multiple-antenna (MIMO) technology is becoming mature for wireless communications and has been incorporated into wireless broadband standards like LTE and WiFi. Basically, the more the number of antennas the transmitter/receiver is equipped with, the more the possible independent signal paths and the better the performance in terms of data rate and link reliability. Massive MIMO (also known as large-scale antenna systems, very large MIMO, hyper MIMO and full-dimension MIMO) makes a clean break with current practice through the use of a very large number of service antennas (e.g., hundreds or thousands) that are operated fully coherently and adaptively. Extra antennas help by focusing the transmission and reception of signal energy into ever-smaller regions of space. This brings huge improvements in throughput and energy efficiency, in particularly when combined with simultaneous scheduling for a large number of user terminals (e.g., tens or hundreds). This Paper focuses on the efficiency of the throughput and fairness of large MIMO. In multi-user MIMO (MU-MIMO), fewer antennas were used, so the only concern was to mitigate the interference of the users. The interference was mitigated by using zero forcing (ZF) receivers while the fairness of the system was maintained by using Rayleigh Fading channel. MU-MIMO was sufficient for only smaller number of users as the number of antennas were fixed and all the users had to be entertained within the same bandwidth. But, in Massive MIMO, along with the interference of the users, the interference of the antennas themselves is also a big concern, as, the number of antennas were increased contrary to the fixed fewer number of antennas in MU-MIMO. Rayleigh Fading channel and ZF receivers were not sufficient for increased number of users and antennas respectively. The problem of interference amongst the antennas was addressed by using regularized channel inversion receivers that increase the throughput of the system while, the fairness of the system is increased by using Nakagami-m channel.

A novel solution based on cognitive heterogeneous networks for removing black spots in TETRA coverage area

Digital Terrestrial Trunked Radio System (TETRA) standard was developed by ETSI to fulfill the rapid changing growth and demands of high bandwidth applications of voice and data required by both PMR and PAMR users. TETRA networks as based on the cellular architecture approach which offers low capital and maintenance cost solution for the deployment of traditional PMR telephony and digital data transmission. TETRA networks are designed on the principle of point to multipoint wireless architecture, which allow it to offer voice and data services at same time to emergency response teams. TETRA network coverage area is affected by the presence of black spots no signal coverage areas where communication between the TETRA mobile user and TETRA base station is not possible. In this paper a technique based on Heterogeneous Cognitive approach with simulations is proposed to eliminate the problem of black spots in TETRA networks.