Mixed Mode Device-to-Device Communication Scheme for Congestion Reduction and Channel Usage Optimization in 5G Cellular Networks

Device-to-Device (D2D) communication schemes have gained more attention in cellular networks particularly in normalization process of the upcoming 5G networks. They have been investigated in core network offloading, congestion reduction and channel usage optimisation.  The two last cases are among the major constraints in current cellular networks and are the main concerns of this paper. The paper presents a mixed mode D2D communication scheme to decentralize data collection between devices and the base station in order to reduce the number of direct connections at the base station of ultra-dense cells characterized by different levels of channel utilizations or target data rates, as expected for 5G networks. The attachment utility is derived as the overall gain of a device for a target data rate and is used as a metric for D2D association’s decision. Results show that the attachment utility and D2D pairs increase by either increasing the D2D communication range or decreasing devices’ target data rates. A further important consideration is that the proposed mixed mode D2D communication scheme improves the throughput expectation in the cell by 14.2% compared to the regular cellular communication.Keywords:     5G Networks, Channel Usage Optimisation, Congestion Reduction, D2D Communication Scheme, Target Data Rate

Comparative Analysis of Multiplicative and Additive Noise Based Automated Regularizations in Non-Linear Diffusion Image Reconstruction

Multiplicative and additive noises are often introduced in image signals during the image acquisition process and result into degradation of image features. The work done by Perona and Malik in 1990 and its modified versions revolutionized the way through which noises or speckles are removed. The Perona-Malik model requires tuning of the regularization parameter to control and prevent staircase artifacts in restored images. The current manual tuning is a challenging and time consuming practice when a long queue of images is registered for processing. Attempt to automate the regularization parameter appeared in Perona-Malik model with self-adjusting shape-defining constant. Although both multiplicative and additive noise based automated regularizations were presented, the paper stayed silent on matters concerning the automation method that fits with speckle reduction. This paper therefore, presents a comparative analysis of additive and multiplicative noise based automated regularizations. Simulation results and paired samples T-tests reveal that the multiplicative noise based automation outperforms the additive noise based automation for small speckle variances. However, the two automation methods do not significantly differ when large speckle variances are assumed

Device–to-Device Association Algorithm for Optimal Neighbour Selection and Channel Sharing in 5G Cellular Networks

The integration of device-to-device (D2D) communication in 5G cellular networks has generated the possibility of multiple transmission modes in a single cell. This has motivated scholars to investigate different mode selection and D2D association algorithms that guarantee the selection of proper transmission mode. However, the complexity of algorithms and tractability of devices in the cell are still remarkably challenging. This paper, therefore, presents a utility based D2D association algorithm that ensures optimal neighbour selection by using numerical linear algebra to minimize computational complexity. Simulation results show that the minimum utility based D2D association increases the expected values of attached devices by 6% and 10% compared to the relative distance and maximum utility based D2D associations, respectively. Alternatively, the throughput expectation increases by 2.5% and 4% compared to the relative distance and maximum utility based D2D associations, respectively. Keywords: Cooperative Communication; D2D, Mode Selection; Relay-assisted; Traffic Overloa