Multiuser Scheduling with Multi Radio Access Selection

Abstract

In this paper we address the problem of multiuser scheduling with multi-radio access selection, i.e., the data flow of a given user can be scheduled over multiple radio access technologies of different operators. We will show that performance gains are possible and come from multiuser diversity as well as multiradio diversity, as both the best user and the best radio access can be selected, at any given time, to get to optimal performance. We compare a terminal-based strategy where users compete to choose the best Radio Access, and a network-based case where the network choose the users to serve at a given time. This work assesses the performance gain due to both multi radio access and multiuser diversity with respect to the no-multi-radio case, where users are constrained to connect to the same single radio access.

Common Radio Resource Management Algorithms for Multimedia Heterogeneous Wireless Networks

“…Table 8 shows the results obtained for the two settings under scenario I when UBReQoS is configured with κ = 0.5 and µ = 1 (other configurations and traffic scenarios show analogous trends). As it can be appreciated, higher satisfaction levels are generally obtained when basing RAT selection decisions on the approximations of equations (10) and (11), with an average satisfaction improvement of 5.1%. Bearing in mind that the channel quality approximation is a more conservative approach, these results can qualitatively be explained as follows.…”

“…In [10], a terminal-based strategy where users compete for the best RAT, and a network-based strategy where the network chooses the users to serve at any given time are compared. The work assesses the performance gain due to both multi-radio access and multi-user diversity with respect to the non-multi-radio case, where users are constrained to connect to the same RAT.…”

SPHERE - A Simulation Platform for Heterogeneous Wireless Systems

“…It characterizes the three radio propagation effects, namely path loss, shadowing and fast fading. (4) Various works have demonstrated the importance of an adequate shadow modeling to conduct appropriate RRM investigations [10]. In fact, the shadowing effect results in additional signal attenuation due to obstacles in the path between transmitter and receiver.…”

“…To conduct their investigations, the authors implemented a simulation tool that takes into account propagation models and some specific RAT-features although it does not model the complete radio transmission process. A different approach was considered in [4] where the authors considered an analytical model that relates the experienced CIR to the user perceived throughput. Nevertheless, the increasing complexity of mobile and wireless communication systems increases the difficulty of studying the performance of new techniques through analytical models.…”

QoS provisioning in beyond 3G heterogeneous wireless systems through common radio resource management algorithms

“…Furthermore, reference [12] also presents other RAT selection principles where the QoS that can be offered by each RAT is also taken into account through the expected transmission rate. The work reported in reference [11] is another example where RAT selection is also based on the expected QoS. A terminal-based strategy where users compete for the best RAT, and a network-based case where the network chooses the users to serve at any given time are compared.…”