Iraqi Journal of Information and communication technology

Huge data rates have been provided by 5G wireless communication systems using a millimetre wave(mm Wave) band that have frequencies ranging from 30 to 300 GHz. mm Wave provides about 10 times the bandwidth used in the existing 4G system. The 5G network deals with a massive number of devices. This presents many challenges including capacity, data rate, end to end delay, and a very large number of connections. In this paper, the main task is to apply network coding to a 5G mm Wave communication system to increase the throughput of the communication links. Simple packet-based network coding schemes using butterfly network topology are simulated. The two network coding schemes considered here are Physical Layer Network Coding (PLNC) and Network Layer Network Coding (NLNC). Models of Additive White Gaussian Noise (AWGN) and mm Wave indoor fading channels are considered in the work using Quadrature Phase Shift Keying (QPSK) modulation. The results of the tests show that the use of both NLNC and PLNC improved throughput in comparison to the un coded system. Using PLNC increased the Bit Error Rate (BER) and the Packet Error Rate (PER), while the NLNC scheme shows almost identical error performance to the un coded system over the mm Wave fading channel. The NLNC presents better throughput performance, measured in Bits/s, by about 14% over the un coded system, whereas in terms of Packets/s, both the network coded and un coded systems have approximately identical throughput performance at very low SNR for the mm Wave channel. At high SNR, the results show that network coding improved throughput when compared to the non-coding case by about 25% at the expense of a slightly increased error rate

By its nature, the server assessed in this study experiences bottlenecking, making load balancing an essential service within the network, particularly for users who increase the load. This paper investigates load-balancing related to software-defined networks (SDNs). Also, three load-balancing algorithms are evaluated and analyzed: the random algorithm (used as a default in Mini net), building and implementing the code of the round-robin algorithm, and building and implementing the code of the weight round-robin algorithm (which depends on two types of servers-namely, python and ruby servers). All evaluations were based on the tools used (i. e. , Ali tool, siege tool, and apache tool). The considered parts constitute three servers, one client, one pox controller, and one open virtual switch. The proposed topology needs to be connected to the pox controller-the Open Flow protocol was utilized. The results show that the random algorithm performed better than the round-robin algorithm, specifically processing time and response time. Also, the round-robin algorithm had a better processing time and response time than the weight round-robin algorithm

Sparse array such as the coprime array is one of the most preferable sparse arrays for the direction of arrival estimation due to its properties, like simplicity, the capability of resolving more sources than the number of elements and resistance to mutual coupling issue. In this paper, a new coprime array model is proposed to increase the degree of freedom (DOF) and improve the performance of the coprime array. The newly designed array can avoid mutual coupling by minimizing the lag redundancy and expand the central lags in the virtual difference co-array. Thus, the proposed structure can resolve more sources than the prototype coprime array using the same number of elements with the improved direction of arrival estimation. Simulation results demonstrate that the proposed array model is more efficient than the other coprime array model

Today, the use of video communication in real-time applications is rising at a rapid rate and most of these videos require secure transmissions like surveillance, video conferencing, video on demand, medical and military imaging systems. The trade-off between data security and real-time performance is the main challenge in this field. This paper presents a protection system that provides a balancing between the security level and coding efficiency. A smart selection for the motion information of the video is done based on canny edge detection scaling which reduces the amount of encrypted data and strong and fast stream encryption is done using key generation model of chaos and RC4 algorithm. The experimental results of the performance metrics confirmed the high perceptual and cryptographic security of the proposed system against attacks and showed that all the requirements of compression efficiency are satisfied