An Examination of the Benefits of Scalable TTI for Heterogeneous Traffic Management in 5G Networks

The rapid growth in the number and variety of connected devices requires 5G wireless systems to cope with a very heterogeneous traffic mix. As a consequence, the use of a fixed TTI during transmission is not necessarily the most efficacious method when heterogeneous traffic types need to be simultaneously serviced.This work analyzes the benefits of scheduling based on exploiting scalable TTI, where the channel assignment and the TTI duration are adapted to the deadlines and requirements of different services. We formulate an optimization problem by taking individual service requirements into consideration. We then prove that the optimization problem is NP-hard and provide a heuristic algorithm, which provides an effective solution to the problem. Numerical results show that our proposed algorithm is capable of finding near-optimal solutions to meet the latency requirements of mission critical communication services, while providing a good throughput performance for mobile broadband services.Comment: RAWNET Workshop, WiOpt 201

Performance Analysis of a System with Bursty Traffic and Adjustable Transmission Times

In this work, we consider the case where a source with bursty traffic can adjust the transmission duration in order to increase the reliability. The source is equipped with a queue in order to store the arriving packets. We model the system with a discrete time Markov Chain, and we characterize the performance in terms of service probability and average delay per packet. The accuracy of the theoretical results is validated through simulations. This work serves as an initial step in order to provide a framework for systems with arbitrary arrivals and variable transmission durations and it can be utilized for the derivation of the delay distribution and the delay violation probability.Comment: ISWCS 201

Resource Optimization with Flexible Numerology and Frame Structure for Heterogeneous Services

We explore the potential of optimizing resource allocation with flexible numerology in frequency domain and variable frame structure in time domain, in presence of services with different types of requirements. We analyze the computational complexity and propose a scalable optimization algorithm based on searching in both the primal space and dual space that are complementary to each other. Numerical results show significant advantages of adopting flexibility in both time and frequency domains for capacity enhancement and meeting the requirements of mission critical services.Comment: 4 page