A novel distributed scheduling scheme for OFDMA uplink using channel information and probabilistic transmission

Distributed uplink scheduling in OFDMA systems is considered. In the proposed model, mobile terminals have the responsibility of making their own transmission decisions. The proposed scheme is based on two dimensional reservation in time and frequency. Terminals use channel state information in order to favor transmissions over certain subchannels, and transmission is done in a probabilistic manner. The proposed approach provides more autonomy to mobile devices in making transmission decisions. Furthermore, it allows avoiding collisions during transmission since it leads to collision detection during the resource reservation phase. The proposed approach is compared to other random access methods and shown to be superior in terms of increasing sum-rate, reducing the number of users in outage, and reducing the collision probability in the reservation phase.     

Performance analysis of a novel traffic scheduling algorithm in slotted optical networks

This paper considers the scheduling problem in a new slotted optical network called Time-Domain Wavelength Interleaved network (TWIN). The TWIN architecture possesses interesting properties, which may offer solutions for next-generation optical networks. Besides, better Quality of Service (QoS) could be achieved in TWIN by minimizing two parameters: queueing delay and delay variance. However, to the best of our knowledge, most of the existing scheduling algorithms in TWIN ignored consideration of QoS and focused mainly on maximizing the throughput. In this paper, we formulate the scheduling problem into an Integer Linear Programming (ILP) problem and propose a novel heuristic – Destination Slot Set (DSS) algorithm to solve it fast and efficiently. Besides, we derive an analytical model for TWIN and investigate the performance of DSS in it. By means of simulations, we demonstrate that our analytical model approximates the TWIN network very well; moreover, DSS incurs smaller queueing delay and delay variance, which ensures better QoS.