Individual packet deadline delay constrained opportunistic scheduling for large multiuser systems

This work addresses opportunistic distributed multiuser scheduling in the presence of a fixed packet deadline delay constraint. A threshold-based scheduling scheme is proposed which uses the instantaneous channel gain and buffering time of the individual packets to schedule a group of users simultaneously in order to minimize the average system energy consumption while fulfilling the deadline delay constraint for every packet. The multiuser environment is modeled as a continuum of interference such that the optimization can be performed for each buffered packet separately by using a Markov chain where the states represent the waiting time of each buffered packet. We analyze the proposed scheme in the large user limit and demonstrate the delay-energy trade-off exhibited by the scheme. We show that the multiuser scheduling can be broken into a packet-based scheduling problem in the large user limit and the packet scheduling decisions are independent of the deadline delay distribution of the packets

Energy Efficient Multiuser Scheduling: Exploiting the Loss Tolerance of the Application

We address the problem of energy efficient scheduling for the loss tolerant applications by exploiting the multiuser diversity. The proposed scheduling scheme allows dropping of a certain predefined proportion of data packets on the transmitter side. However, there is a hard constraint on the maximum number of successively dropped packets. The scheduler exploits average data loss tolerance to reduce the average system energy expenditure while fulfills the hard constraint on successively dropped packets. We analyze the scheme using asymptotically large user limit. The numerical results illustrate the energy efficiency of the scheme as a function of the average packet drop probability and the maximum permitted successively dropped packets parameters

Energy Efficient Multiuser Scheduling: Exploiting the Loss Tolerance of the Application

We address the problem of energy efficient scheduling for the loss tolerant applications by exploiting the multiuser diversity. The proposed scheduling scheme allows dropping of a certain predefined proportion of data packets on the transmitter side. However, there is a hard constraint on the maximum number of successively dropped packets. The scheduler exploits average data loss tolerance to reduce the average system energy expenditure while fulfills the hard constraint on successively dropped packets. We analyze the scheme using asymptotically large user limit. The numerical results illustrate the energy efficiency of the scheme as a function of the average packet drop probability and the maximum permitted successively dropped packets parameters

Energy Efficient Reduced Complexity Multi-Service, Multi-Channel Scheduling Techniques

The need for energy efficient communications is essential in current and next-generation wireless communications systems. A large component of energy expenditure in mobile devices is in the mobile radio interface. Proper scheduling and resource allocation techniques that exploit instantaneous and long-term average knowledge of the channel, queue state and quality of service parameters can be used to improve the energy efficiency of communication. This thesis focuses on exploiting queue and channel state information as well as quality of service parameters in order to design energy efficient scheduling techniques. The proposed designs are for multi-stream, multi-channel systems and in general have high computational complexity. The large contributions of this thesis are in both the design of optimal/near-optimal scheduling/resource allocation schemes for these systems as well as proposing complexity reduction methods in their design. Methods are proposed for both a MIMO downlink system as well as an LTE uplink system. The effect of power efficiency on quality of service parameters is well studied as well as complexity/efficiency comparisons between optimal/near optimal allocation