NIST PREP Opportunity in Wireless Communication Algorithms
The Wireless Networks Division-673 of the National Institutes of Standards and Technology (NIST) is seeking qualified applicants for a research position on the project: Admission Control and Scheduling in IEEE 802.11ad/ay MAC.
The position is available through NIST’s Professional Research Experience Program (https://www.nist.gov/iaao/academic-affairs-office/nist-professional-research-experience-program-prep).
IEEE 802.11ad/ay is the new standard in WiFi that operates in the mmWave band (60 GHz). It provides high data rate and Quality of Service (QoS) by having contention-free media access mechanism called Service Period (SP). The 802.11ad/ay standards does not specify any admission control or scheduling algorithm for the user traffic. The standard supports two types of traffic: isochronous and asynchronous. Users describe their traffic using Traffic Specification (TSpec) and send their requests to allocate resources to the Access point (AP). If the request is accepted by the AP then it must ensure that the resources are guaranteed to be available to the users.
Thus, admission control and scheduling play a vital role in the 802.11ad/ay network. In this project, we will design, implement and evaluate different admission control and scheduling algorithms for 802.11ad/ay network that uses traditional analytical model-based approach. The implementation will be in the ns3 simulator and/or in Python. In the second phase of the project, we will use Artificial Intelligence (AI)/Machine Learning (ML) based methods to design and evaluate admission control and scheduling of IEEE 802.11ad/ay user traffic.
- Must be a graduate student majoring in Computer Science or Electrical Engineering or a closely related field (at a minimum, a B.S. holder).
- Must have experience in programming in Python and C++ and knowledge of computer algorithms.
- Available for research, up to 20 hours per week, beginning in August or September of 2021. (Note: research on this project will be conducted remotely and interactions will be through virtual meetings).
- Experience with network simulator (e.g., ns3) and knowledge of wireless networks and AI/ML (along with programming in tensorflow/keras/pytorch) are desirable.
Qualified applicants should submit a CV and cover letter to Dr. Anirudha Sahoo (firstname.lastname@example.org).
For questions related to the nature of research and work required, contact Dr. Sahoo (email@example.com).