Search

In this paper, we present an analytical framework for the performance evaluation of a pre-emptive priority scheduler in multi-resource networks, like those using Orthogonal Frequency Division Multiple Access (OFDMA). We focus on Quality of Service (QoS)-guaranteed traffic for which QoS is guaranteed to individual users by restricting the number of admitted users. For this, the QoS-constrained capacity, in terms of the number of supported users, needs to be ascertained a priori. The QoS-constrained capacity is a function of users’ QoS requirements, channel conditions, and radio resource allocation algorithms, which in this work is the pre-emptive priority scheduler. It is, thus, a variable quantity and mostly obtained using time-consuming offline computer simulations. Mathematical models, on the other hand, are timely and accurate, allowing the capacity to be derived in real-time as a function of the current network configuration. Existing works on mathematical modelling of pre-emptive priority schedulers have mostly focussed on single servers or multiple servers where a single server is assigned to each user. In contrast, OFDMA networks have multiple radio resources, i.e., multiple servers and each user may need more than one radio resource for a single packet transmission, i.e. it is a multi-resource system, which has been accounted for in this paper. We classify the users based on their resource requirements and model the pre-emptive priority scheduler as a multi-class, multi-server, multi-resource, non-work conserving queueing system. We derive its QoS metrics like average delay, packet drop probability, throughput, etc., from its continuous-time Markov Chain. We then use the derived QoS metrics to obtain the QoS-constrained capacity and design a threshold based predictive call admission control unit. We have validated the results using extensive discrete event simulations.

This poster presents the design, development and test results of an energy consumption analysis module developed over ns3 Millimeter Wave (mmWave) communication for analyzing power consumption for 5G New Radio (NR) User Equipment (UE) during both continuous and discontinuous packet receptions. This module is important to analyze and explore the energy consumption behavior of the 5G communication protocols under the NR technology. The developed module includes the complete Radio Resource Control (RRC) state machine for 5G NR recommended by 3GPP Specification 38.840. To the best of our knowledge, the designed module is the first of its kind that provides a comprehensive energy analysis for the 5G NR UEs over mmWave communication.

In this paper, we present an analytical framework for the performance evaluation of Radio Resource Allocation (RRA) in Orthogonal Frequency Division Multiple Access (OFDMA) networks. We focus on Quality of Service (QoS) guaranteed traffic whose capacity, in terms of the number of active user connections, depends on the users’ QoS requirements and channel conditions, and the RRA algorithm. The required QoS is guaranteed by restricting the number of admitted calls, which in turn requires an accurate estimate of the QoS metrics and capacity supported by the RRA when a new call arrives. These estimates for OFDMA networks are variable and usually obtained through time-consuming offline computer simulations. Mathematical frameworks on the other hand yield timely and accurate results. However, earlier known works on analytical modelling of RRA either consider a single channel with random traffic arrivals or multiple channels with full buffer data traffic. In contrast, we develop a queueing theoretic framework considering randomly arriving QoS-guaranteed traffic in a variable-rate multi-channel multi-class OFDMA network. The framework can be used online leading to better dynamic Call Admission Control. We characterize the RRA algorithm using a scheduler control parameter which can regulate the call blocking probability while providing predefined QoS constraints. We model the RRA as a variable service rate, multi-server, multi-class, finite buffer queueing system and verify the derived QoS metrics using extensive Monte-Carlo discrete event simulations.

Orthogonal Frequency Division Multiple Access based 4G cellular systems are designed to support different types of traffic through packet switching only. Hence, packet schedulers are important in increasing Real-Time (RT) traffic capacity as well as non Real-Time (nRT) data throughput of these networks without violating control channel and Quality of Service (QoS) constraints. Increasing capacity and maintaining QoS being conflicting design objectives, a desired Mixed Traffic Scheduler (MTS) algorithm is expected to yield a suitable trade-off between them. In order to identify such an algorithm for any ratio of RT and nRT users in a cell, in this paper, we compare the performance of certain MTS algorithms in terms of number of supportable users, data throughput, control channel usage, and resource usage. We propose two MTS algorithms which treat voice and video as a single traffic class. These are: (1) dynamic packet scheduling and (2) a new limited Joint Time Frequency (JTF) scheduling. These algorithms are compared with known ones like Modified Largest Weighted Delay First (Andrews et al. in IEEE Commun Mag 39(2):150---154, 2001) and SP-Dynamic (SemiPersistent for VoIP and Dynamic for Video) (Muntean and Otesteanu 2011). Impact of bundling voice and video packets on the performance of the algorithms is also investigated. Extensive system level simulations show that in addition to 14 video users per MHz, the proposed JTF scheduling with bundled VoIP and video packets can support 57.5 % more VoIP users per MHZ than the 3GPP requirement for only VoIP traffic (ITU-R 2008).

In this work, we propose a real-time traffic scheduler framework that is generalized to handle both voice and video in the downlink of Orthogonal Frequency Division Multiple Access (OFDMA) based cellular networks like 3GPP Long Term Evolution (LTE). These networks are packet switched in nature. As a result, Packet Scheduling (PS) and Radio Resource Allocation (RRA) algorithms at the Base Station (BS) play an important role in achieving high capacity. The paper, thus, proposes a new RRA algorithm which combines time domain PS and frequency domain RRA, thereby increasing the system capacity of both VoIP and video users. The algorithm is also seen to improve the percentage user satisfaction while keeping the radio resource utilization nearly unchanged. Its performance is analyzed using LTE system parameters and evaluated according to ITU-R specified methodologies. Results of key performance indicators such as system capacity, scheduling delay, Physical Resource Block (PRB) utilization, percentage user satisfaction are shown.