Resource Allocation in Uplink Long Term Evolution

One of the most crucial goals of future cellular systems is to minimize transmission power while increasing system performance. This master thesis work presents two channel-queue-aware scheduling schemes to allocate channels among active users in uplink LTE. Transmission power, packet delays and data rates are three of the most important criteria critically affecting the resource allocation designs. Therefore, each of these two scheduling algorithms proposes a practical method that assigns resources in such a way so as to optimally maximize data rate and minimize transmission power and packet delays while ensuring the QoS requirements. After converting the resource allocation problem into an optimization problem, the objective function and associated constraints are derived. Due to the contiguity constraint, which is imposed by SC-FDMA in uplink LTE, binary integer programming is employed to solve the optimization problem. Also the heuristic algorithms that approximate optimal schemes are presented to decrease the algorithm complexity

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