Document Type


Date of Degree

Spring 2017

Degree Name

PhD (Doctor of Philosophy)

Degree In

Electrical and Computer Engineering

First Advisor

Raghuraman Mudumbai

Second Advisor

Soura Dasgupta

First Committee Member

Er-Wei Bai

Second Committee Member

Anton Kruger

Third Committee Member

Ralph P. Russo


Constant evolution requirements of Wi-Fi and cellular standards to meet the demands of better power efficiency, longer range and higher throughput of wireless networks has drawn attention to multiple antenna transmitters and receivers, i.e., multi-input multi-output(MIMO) systems. This research falls in the larger context of distributed MIMO, or DMIMO systems, wherein groups of cooperating transceivers organize themselves into virtual antenna arrays which can, in principle, emulate any MIMO technique that a centralized array can support.

Beamforming and nullforming are techniques that can be employed by centralized or distributed antenna array, and can be building blocks for MIMO communication systems; these impart directionality to the array and can help cater to the demands of today's wireless networks. In beamforming, a set of distributed transmitters in a wireless network cooperatively transmit a common message signal in such a way that their individual transmissions add up to a desired SNR level at the set of designated receivers while in nullforming, cooperative transmission ensures that the individual transmissions cancel each other at the set of designated receivers. The key bottleneck in the practical realization of DMIMO is synchronization. Distributed nullforming specifically poses challenges that call for special attention. Here, we develop a set of scalable algorithms for beamforming and nullforming using distributed transmitters by forming a virtual antenna array and overcome the involved challenges in a purely distributed fashion.

Under a per-antenna power constraint and assuming equal-gain channels, an ideal N-antenna beamformer provides an N squared-fold coherent power gain on target. Ideal nullforming on the other hand results in zero power on the target. These properties motivate applications in cooperative jamming or communications, where the goal is to maximize the net transmitted power using multiple transmitters while simultaneously protecting a designated receiver. For example, in a cognitive radio system where the transmit array is a secondary user of licensed spectrum which seeks to communicate with a set of secondary receivers (beam targets) without causing any interference at primary receivers (null targets). Another possible application is a cellular network where adjacent Base Stations form a transmit array and coordinate their transmissions to avoid cochannel interference. Recent algorithms on wireless security critically rely on nodes blanketing a landscape with full power jamming signals while protecting a cooperating receiver through nullforming. So a third application can be electronic warfare where a transmit array broadcasts strong jamming signals that disable an enemy's communication infrastructure while protecting friendly stations (null targets) from interference due to the jamming signal. The joint beam and nullforming specifically can be more generally thought of as a fundamental building block for increased spatial spectrum reuse and toward achieving the full spatial multiplexing gains available from MIMO techniques with distributed antenna arrays.


algorithms, beamforming, distributed antenna array, MIMO, nullforming, wireless communication


xi, 110 pages


Includes bibliographical references (pages 105-110).


Copyright © 2017 Amy Kumar