Design and Analysis of Multilevel Coding Scheme with Cooperative Diversity for Improved System Performance

Abstract

The next generation communication systems aim at providing higher data rate, enhanced spectral efficiency, improved coverage and lower latency for the connection of billions of wireless devices. The rising demand of reliable wireless communication requires an innovation in the wireless technology. In this research work, multilevel coding scheme in conjunction with cooperative diversity is investigated in an endeavor to meet these requirements. The cooperative multilevel coding system provides a significant improvement in performance over non-cooperative multilevel coding system. The proposed system considers various mobile nodes communicating with a common destination node. Due to broadcast nature of wireless medium, each mobile node can overhear the information transmitted by other mobile nodes to the common destination node. The mobile nodes act as cooperative nodes by sharing their antennas in order to transmit their own information as well as the information of neighboring nodes. Each mobile node encodes the overheard information along with its own information using multilevel coding scheme and transmits the coded information to common destination node. This creates a different form of transmit diversity, known as cooperative diversity. In this way, the destination node receives the information of each mobile node as many times as there are number of cooperative nodes. The proposed cooperative communication system is investigated for various error-correcting codes such as convolutional codes, pseudo space-time trellis codes (PSTTC), weighted space-time trellis codes (WSTTC), and dynamic space-time trellis codes (DSTTC). These codes are used as component codes in the multilevel coding scheme. The cooperative multilevel convolutional coding system is designed for single antenna mobile nodes. Each cooperative mobile node employs multilevel coding scheme with convolutional codes as component codes to generate the coded symbols. The multilevel convolutional coded symbols are mapped and transmitted to destination