Receiver Concepts and Resource Allocation for OSC Downlink Transmission

TL;DR

This paper introduces new receiver techniques and resource allocation algorithms to enhance the capacity and performance of OSC downlink transmission in GSM VAMOS systems, addressing challenges of single-antenna mobile stations.

Contribution

It presents novel receiver concepts for channel estimation, user separation, and equalization, along with a joint power and resource allocation algorithm for improved system capacity.

Findings

Proposed channel estimation algorithms outperform existing methods.

New equalization schemes significantly improve signal quality.

Joint power and resource allocation algorithms enhance system capacity in simulations.

Abstract

Voice services over Adaptive Multi-user channels on One Slot (VAMOS) has been standardized as an extension to the Global System for Mobile Communications (GSM). The aim of VAMOS is to increase the capacity of GSM, while maintaining backward compatibility with the legacy system. To this end, the Orthogonal Sub-channels (OSC) concept is employed, where two Gaussian minimum-shift keying (GMSK) signals are transmitted in the same time slot and with the same carrier frequency. To fully exploit the possible capacity gain of OSC, new receiver concepts are necessary. In contrast to the base station, where multiple antennas can be employed, the mobile station is typically equipped with only one receive antenna. Therefore, the downlink receiver design is a very challenging task. Different concepts for channel estimation, user separation, and equalization at the receiver of an OSC downlink transmission are introduced in this paper. Furthermore, the system capacity must be improved by suitable downlink power and resource allocation algorithms. Making realistic assumptions on the information available at the base station, an algorithm for joint power and radio resource allocation is proposed. Simulation results show the excellent performance of the proposed channel estimation algorithms, equalization schemes, and joint radio resource and power allocation algorithms in realistic VAMOS environments.