Low Complexity Fair Scheduling in LTE/LTE-A Uplink Involving Multiple Traffic Classes

Abstract

Long term evolution (LTE) has already been accepted as the de-facto 4G wireless technology. However, the bulk of the research on LTE packet scheduling is concentrated in the downlink and the uplink is comparatively less explored. In uplink, mostly channel aware scheduling with throughput maximization has been studied. Further, channel aware scheduling requires an infinitely backlogged buffer model. This makes the investigations unrealistic. Therefore, in this work, we propose an LTE uplink packet scheduling procedure with a realistic traffic source. Firstly, we advocate a joint channel and buffer aware algorithm, which seeks to maximize the actual number of bits transmitted once a user is scheduled. Thereafter, we modify our algorithm to support traffic types with delay constraints. Next, we enhance our algorithm to support multiple classes of traffic. Finally, we have introduced priority flipping to minimize bandwidth starvation of lower priority traffics in presence of higher percentage of high priority traffic. In all the proposals, we have replaced the delay constraint by minimizing the packet drop due to delay violation. This further helps in reducing the problems to a well-known assignment problem.

Energy Efficiency Optimization for Backscatter Enhanced NOMA Cooperative V2X Communications Under Imperfect CSI

“…One of the critical issues is the massive connectivity in B5G V2X networks which might not be possible through the existing orthogonal spectrum access resources, resulting in traffic and data congestion [10]. Another challenge is the fair and efficient resource allocation among large scale devices [11], [12]. Thus, new spectrum access technologies would be required to provide high spectral efficiency and support massive connectivity in B5G V2X networks.…”

Optimized two‐level scheduler for video traffic in LTE downlink framework

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