Master's Thesis

Distributed Spatial Multiplexing in a Wireless Multi-hop Network


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Wireless Networks. The interest in wireless ad hoc networks has recently grown due to their low deployment costs and the potential to build self-organizing heterogenous and pervasive wireless networks. Application examples are wireless personal area networks, home networks or wireless sensor networks. An ad hoc wireless network is a collection of wireless mobile nodes that form a network without a prescribed infrastructure. In contrast to cellular systems the mobiles handle the necessary networking tasks by themselves through the use of distributed protocols and control algorithms. Multi-hop connections, whereby intermediate nodes relay the message to the final destination are mandatory to achieve connectivity, enhance transport capacity and power efficiency.

MIMO. Multiple antennas at transmitter and receiver introduce spatial degrees of freedom into a wireless communication system. Space-time signal processing utilizes these degrees of freedom to boost link capacity and/or to enhance link reliability of multiple-input multiple-output (MIMO) communication systems. A system with M transmit and N receive antennas constitutes a MxN MIMO channel. For i.i.d. Gaussian channel coefficients the ergodic capacity of a MIMO channel scales linearly with min{M,N}. With a spatial multiplexing architecture one can achieve the ergodic capacity without additional cost of bandwidth or power by transmitting data streams simultaneously over spatial sub-channels which are available in a rich scattering channel.

Distributed MIMO in Wireless Networks. Node cooperation at the physical layer (PHY) is the natural extension of space-time processing to multiple distributed nodes in an ad hoc network. The most basic form of PHY node cooperation is linear amplify-and-forward relaying. The relays receive the signal from the source in the first time slot and forward an amplified version in the second time slot. This way of relaying leads to low-complexity relay transceivers and to lower power consumption since there is no signal processing for decoding procedures. Another possibility is decode-and-forward relaying, where a relay fully decodes the incoming source signal, re-encodes the acquired information symbols and re-transmits the information signal either to the next relay or to the final destination. We refer to distributed spatial multiplexing when the simultaneous transmission of independent data streams is supported by spatially distributed network nodes assisting the communication between source and destination.

Problem Formulation. In this project you will study specific transmission algorithms (MIMO tunnel, multi-path routing) for wireless multi-hop networks. In particular you will evaluate the performance (achievable data rates, error probabilities) of different signaling strategies as amplify-and-forward and decode-and-forward by means of analysis, simulation (MATLAB) and verification (RACooN testbed).


Subject area Wireless relay networks, distributed MIMO communication systems
Type of work 30% Theory, 30% MATLAB, 40% Measurements
Supervisors Dr. Boris Rankov, Dr. Stefan Berger
Students Bernhard Bicher, Mirsad Cekic
Professor Prof. Dr. Armin Wittneben