The Wireless Innovation Laboratory (WI Lab) at the WPI Department of Electrical and Computer Engineering possesses both expert personnel and state-of-the-art facilities for designing and prototyping wireless communication systems using either computer simulation packages or software-defined radio programmable wireless platforms. Moreover, under the NSF grant 0754315 – “WN: Quantification of Spectrum Availability for Wireless Network Access”, the lab is equipped with wireless spectrum measurement equipment for research investigations in the 0-3 GHz frequency range. Finally, the lab is equipped with twenty USRP experimental software-defined radio platforms (two version 1.0 units, fourteen version 2.0 units, and four version N210 units from Ettus Research LLC) for wireless networking prototyping and experimentation. Specifically, the WILab includes the following equipment:

  • 12 computer workstations
  • 2 USRP (Version 1) software-defined radio platforms
  • 14 USRP (Version 2) software-defined radio platforms
  • 15 USRP (Version N210) software-defined radio platforms
  • 1 Agilent CSA N1996A 0-3 GHz spectrum analyzer (with battery packs)
  • 1 Mini-discone antenna (100 – 1600 MHz, with 3’ tripod)
  • 1 WG horn antenna (0.7 – 18.0 GHz, with tripod)
  • 1 Xilinx Virtex 5 HW-V5-ML506-UNI-G Prototyping Board
  • 25 complete licenses of MATLAB and Simulink with associated toolboxes and blocksets
  • 1 OPNET license

In addition to the resources available at the WI Lab, the WPI Department of Electrical and Computer Engineering staffs an electronics shop with three full time technicians, and the expected array of equipment and parts. Furthermore, the department has systems support staff which perform backups and maintain the operating systems. These efforts are coordinated by a senior network operations officer.

WPI Computing and Communications Center (CCC) is responsible for both the installation and maintenance of the general telecommunication infrastructure deployed across campus. This data network on the main campus consists of a 10 Gigabit Ethernet backbone which connects 30 academic buildings, 2 satellite campuses, and 28 dorms, fraternities, and sororities. WPI commodity Internet connections are via gigabit Ethernet lines to ProSpeed, Charter Communications, and Sprint, with service levels set at 100 Megabits/sec. WPI CCC peers with Charter Communications at 474 Main Street such that cable modem users have a more direct connection to WPI, and to the others who connect to the WPI gigaPoP. Furthermore, WPI has an OC3 link (155 Megabits/sec) to the Northern Crossroads (NoX) to gain access to Internet2 on the Abilene network. To accomplish this connection, WPI CCC operates a Juniper router at One Summer Street in Boston. WPI CCC Network Operations (NetOps) manages networking for approximately 17,000 devices, and maintains approximately 2.75 million feet of copper cable and 700,000 feet of fiber.

In terms of software resources, MATLAB software is available at WPI for student use either on campus or accessed remotely via VPN connection. There are currently 150 user concurrent licenses, in addition to 10 (soon to be 30) standalone licenses for faculty and staff on travel, available at WPI. Furthermore, WPI has GNU Fortran and C on all linux/Unix servers and workstations. WPI has Intel Compilers on most of the research Linux/Windows servers and Portland Group Compilers on selected Linux Servers.


Spectrum Query Utility Interface for Realtime Radio Electromagnetics Web Interface

To provide the rest of the international research community with access to wireless spectrum measurements via the Internet, where frequency bands anywhere within 100 MHz to 3 GHz can be scanned according to a set of specifications, and the data can be retrieved in text file format from the web server, Spectrum Query Utility Interface for Real-time Radio Electromagnetics Web Interface (SQUIRRELWeb) can be freely employed on a first-come first-serve basis. To use SQUIRRELWeb, click here for access to the website.

Dynamic Spectrum Access Networks and Wireless Network Security Research using OPNET

This research mainly focuses on QoS routing in dynamic spectrum accessing (DSA) networks. New transmission technologies such as cognitive radio applied in DSA networks enable agile transmissions and provide larger transmission capacity. Nodes within DSA networks possess more information about the surrounding wireless spectrum within the vicinity and are thus able to choose an appropriate frequency band for transmission. In this research, we are trying to devise a collection of QoS routing algorithms that can efficiently utilize the wireless spectrum information in order to reach higher throughput values and lower latency penalties for DSA networks. In particularm, we are developing an algorithmic approach where each node is operating according to its local wireless spectrum information while simultaneously achieving a near-optimal routing path and spectrum allocation. This research is supported in part by the OPNET University Programs.

NSF Award #1547291 “EARS: Adaptive Behavioral Responses for Dynamic Spectrum Access-Based Connected Vehicle Networks”

nsfThis research project studies how dynamic spectrum access (DSA)-based vehicular networks can be combined with bumblebee foraging theory concepts. Although wireless networking research has previously looked to the insect world for insights on real-time decision-making across multiple communication nodes within a network in order to achieve some level of distributed optimization, e.g., ant colony optimization, honeybee swarm techniques, all of these approaches significantly depend on the high level of social dependency and information exchange found in these species in order to perform these operations. Conversely, bumblebees have been characterized as socially sharing past and present information with other bumblebees, but are still capable of making independent decisions, which is very similar to nodes within a vehicular networking environment. The application of mathematical tools used to temporally weigh the information shared between vehicular networking nodes as well as predict conditions in the near-future, such as autoregressive moving average (ARMA) filters and Kalman filters, have never been employed in models used to describe bumblebee behavior. Consequently, this effort could make an impact on biological sciences by providing mathematical tools that can be employed during the information weighing process of bumblebees. Click here for more information about this project.