Introduction

Chapter
Part of the Foundations in Signal Processing, Communications and Networking book series (SIGNAL, volume 8)

Abstract

The broadcast channel is an integral entity of many wireless network topologies and denotes the downlink transmission from a central base station to several decentralized users. During the formation phase of the first wireless networks, only few subscribers were joining the network and voice telephony was the dominant service offered. Due to the consequently small rate requirements, the network load was expected to be small such that it was possible to employ orthogonal multiple access techniques to serve the different users in the broadcast channel. However, the increasing number of subscribers and the arising amount of multimedia data led to the insight that orthogonal access schemes do not fully exploit the available degrees of freedom that are offered by the scarce resources power and frequency bandwidth. One step to cope with the higher network load is to allow for some interference in a controlled way instead of completely suppressing it, a method which enhances the efficiency of the system. Obviously, higher data rates can also be offered by using a broader frequency band for the communication but due to regulations or the high expenses, this is not always possible. A second step to meet the increased demand for high data rate communication of a growing number of subscribers is the application of multiple antennas which enhance the spectral efficiency without having to spend more power or bandwidth. Due to the asymmetry of the data traffic in the uplink and the downlink, multi-antenna element base stations play a central role in the broadcast channel as the amount of downlink traffic exceeds the uplink traffic by far.

Keywords

Channel State Information Broadcast Channel Perfect Channel State Information Multiple Access Channel Dirty Paper Code 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Technische Universität München, Fachgebiet Methoden der SignalverarbeitungMünchenGermany

Personalised recommendations