Decentralized Interference Alignment for Tactical Wireless Networks: From Theory to Practice

Abstract

In the initial phase, interference alignment concepts are explored at the network layer us- ingnetwork alignment. The implementation of network alignment at this phase is performed usingAndroid devices attached to the Proteus III robots from the Pharos Lab to replicate mobileenvironments. This phase produces a first attempt at implementation of interference alignmentconcepts on the Pharos platform and lays the foundations for exploring topologies where interferencealignment is feasible.Once network alignment experiments are concluded, the second phase moves on to the physicallayer. In order to implement interference alignment techniques at this layer, spe- cializedequipment with accessible radio stacks is required. The efforts of the second phase focus on thedevelopment and prototyping of special coding and alignment techniques that need to betransmitted over the air. The FlexRIO software defined radio (SDR) platform provides the requiredflexibility to implement, test, and iterate over different techniques in a controlled environment. Usingthe FlexRIO FPGA Module along with 4 transceiver adapter modules allows us to create interferencenetworks where interference alignment is feasible (the smallest feasible case for interference alignmentrequires 3 users). This module also provides a well-supported software development platform andlibraries that make the implementation process more accessible and more robust. While theFlexRIO provides excellent flexibility and a wide range of rapid prototyping resources, it has a bulkyform factor that prevents it from being used in mobile environments.In the third phase, the work concentrates on taking the techniques developed on thecontrolled static environment using the FlexRIO and moving them to the mobile environment. Usingthe Pharos testbed as ourmobile platform, we choose to attach universal software radio peripherals(USRP) to the Proteus III robots and use them as agents in our mobile network. The USRPchosen isthe NI USRP-2942R SDRwhich has the required computational power to execute the schemesdeveloped on the FlexRIO. The reconfigurable FPGA on these devices is a key part of this effortsince interference alignment applications inherently require low- latency. The mentioned USRPs alsoworks under the same development environment as the FlexRIO which facilitates the transfer oftechniques from the static to the mobile setting. Due to their smaller size, the USRPs can be loadedonto the robots where outdoor experiments in large areas can be perform providing a realistic modelof end-user applications.The list of equipment presented satisfies the required elements to take interference alignmenttechniques and ideas from exploration at the network later to development and proto- typing atthe physical layer to, ultimately, implementation in a realistic mobile environment. The use of thisequipment combined with the already available resources, including those of the Pharos Lab, providea rich deployment setting where advanced interference alignmenttechniques can be developed and thoroughly evaluated.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 07, 2017
Source ID
N000141512682

Entities

People

  • Sriram Vishwanath

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Texas at Austin

Tags

Fields of Study

  • Computer science

Readers

  • Aerospace Engineering
  • Distributed Systems and Data Platform Development

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control