Clustering Optimization for Out-of-Band D2D Communications

Significant increase in multimedia traffic challenges 5G networks in terms of capacity and correspondent QoS parameters. Device-to-device communication paradigm has already become an integral part of 3GPP standards; nevertheless it has not yet been widely deployed due to many different reasons. D2D is expected to leverage implementation of many qualitatively new services and to efficiently accomplish it D2D devices are supposed to form clusters. Due to practical limitations, current D2D implementations are mostly out-of-band and use Wi-Fi Direct. In this paper, we propose a novel model for throughput optimization in out-of-band D2D clusters. We delivered numerical results for different typical cluster member distributions and revealed key functional dependencies. Further, for the first time we compare clustering algorithms for out-of-band D2D and identify effective clustering algorithm that increases network resource utilization rate

Clustering optimization for out-of-band D2D communications

Significant increase in multimedia traffic challenges 5G networks in terms of capacity and correspondent QoS parameters. Device-To-device communication paradigm has already become an integral part of 3GPP standards; nevertheless it has not yet been widely deployed due to many different reasons. D2D is expected to leverage implementation of many qualitatively new services and to efficiently accomplish it D2D devices are supposed to form clusters. Due to practical limitations, current D2D implementations are mostly out-of-band and use Wi-Fi Direct. In this paper, we propose a novel model for throughput optimization in out-of-band D2D clusters. We delivered numerical results for different typical cluster member distributions and revealed key functional dependencies. Further, for the first time we compare clustering algorithms for out-of-band D2D and identify effective clustering algorithm that increases network resource utilization rate. © 2017 A. Paramonov et al

Optimization of IEEE 802.11e access class parameters with cross-layer approach

The aim of this paper is to analyze the performance of diverse applications in a wireless scenario based on the IEEE 802.11e standard. In particular, TCP-based traffic (several TCP versions will be used, such as: TCP NewReno, SACK, and Westwood+) and UDP-based traffic will be considered referring to FTP download and VoIP applications, respectively. Tests carried out in the ns-2 environment have permitted to evaluate quality of service issues and the cross-layer impact on the transport layer due to EDCA parameters. The interest is here on the selection of the contention window sizes for different IEEE 802.11e access classes in order to guarantee a good performance for both TCP-based and UDP-based traffic flows

An analytical evaluation of VoD traffic treatment within the EF-enabled diffserv ingress and interior nodes

Abstract -The differentiated services (DiffServ, [1]) expedited forwarding (EF, [2]) per-hop behavior (PHB) is targeted on applications which need strict guarantees of end-to-end delay and should not suffer from packet losses. It makes EF PHB an appropriate choice for lossfree timely delivery of delay and loss intolerant traffic. It is expected that the substantial part of such sort of traffic will be generated by video-on-demand (VoD) services. In order to provide transmission service which is based on EF PHB to VoD traffic, several traffic conditioning functions have to be implemented within the DiffServ ingress nodes. These conditioning functions are based on traffic profiles. In this paper we show how to compute EF PHB traffic profiles for VoD traffic, which are based on simple token bucket mechanism and consider the effect of traffic profile violations. We evaluate both aggregated traffic and per-source quality of service (QoS) degradations caused by traffic profile violations. In order to compute the parameters of EF PHB queue within the DiffServ ingress node we approximate the output stochastic process from the first queuing system by arrival curve. We also consider the VoD traffic treatment within DiffServ interior nodes and show how to compute parameters of EF queues within those nodes

Analytical approximations for interference and SIR densities in terahertz systems with atmospheric absorption, directional antennas and blocking

Researchers face fundamental challenges applying the stochastic geometry framework to analysis of terahertz (THz) communications systems. The two major problems are the principally new propagation model that now includes exponential term responsible for molecular absorption and blocking of THz radiation by the human crowd around the receiver. These phenomena change the probability density function (pdf) of the interference from a single node such that it no longer has an analytical Laplace transform (LT) preventing characterization of the aggregated interference and signal-to-interference ratio (SIR) distributions. The expected use of highly directional antennas at both transmitter and receiver adds to this problem increasing the complexity of modeling efforts. In this paper, we consider Poisson deployment of interferers in ℜ2 and provide accurate analytical approximations for pdf of interference from a randomly chosen node for blocking and non-blocking cases. We then derive LTs of pdfs of aggregated interference and SIR. Using the Talbot's algorithm for inverse transform we provide numerical results indicating that failure to capture atmospheric absorption, blocking or antenna directivity leads to significant modeling errors. Finally, we investigate the response of SIR densities to a wide range of system parameters highlighting the specific effects of THz communications systems. The model developed in this paper can be used as a building block for performance analysis of realistic THz network deployments providing metrics such as outage and coverage probabilities. © 201

Clustering optimization for out-of-band D2D communications

Significant increase in multimedia traffic challenges 5G networks in terms of capacity and correspondent QoS parameters. Device-To-device communication paradigm has already become an integral part of 3GPP standards; nevertheless it has not yet been widely deployed due to many different reasons. D2D is expected to leverage implementation of many qualitatively new services and to efficiently accomplish it D2D devices are supposed to form clusters. Due to practical limitations, current D2D implementations are mostly out-of-band and use Wi-Fi Direct. In this paper, we propose a novel model for throughput optimization in out-of-band D2D clusters. We delivered numerical results for different typical cluster member distributions and revealed key functional dependencies. Further, for the first time we compare clustering algorithms for out-of-band D2D and identify effective clustering algorithm that increases network resource utilization rate. © 2017 A. Paramonov et al