Evolutionary Computation in Scheduling

5Computationally Efficient Scheduling Schemes for Multiple Antenna Systems Using Evolutionary Algorithms and Swarm Optimization

Prabina Pattanayak¹ and Preetam Kumar²

¹ Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Assam, Silchar, India

² Department of Electrical Engineering, Indian Institute of Technology Patna, Bihar, Patna, India

5.1 Introduction and Problem Statement Formulation

In this section, different problem statements/scenarios of multi‐antenna wireless communication systems are discussed, where GA and PSO have been implemented to provide computationally efficient scheduling schemes. Also, an introduction to these problem statements/scenarios is presented for understanding the background.

Single‐antenna systems offer less system capacity as they can transmit data to only one user instantaneously. The system capacity enhancement of wireless systems and lower delay wireless packet data systems is achieved by multi‐user multiple‐input multiple‐output (MU‐MIMO) systems by transmitting data to several users, as many as the number of antennas at the base station (BS) without requiring additional bandwidth or transmit power. This simultaneous data transfer by BS to a number of users is proposed in a dirty paper coding (DPC) scheme. Hence, BS always searches for a subset of users who are the best in channel conditions. To accomplish this activity, BS needs full channel state information (CSI) of every user in the reverse ...