Wireless & Signal Processing Lab (WiSP) undertakes research projects related to wireless communication, signal and image processing and radio frequency (RF) systems design.
The researchers explore theoretical as well as experimental aspects of wireless communication. Software-defined radios are used to experiment on the PHY and MAC layers of advanced radio technologies including Wi-Fi, LTE, LoRa etc. Machine learning is applied for PHY layer and MIMO processing. Some other research areas include Non-orthogonal waveform, full duplex massive MIMO, context/socially aware wireless networks, optimization in 5G communication, small cell and moving small cell network and D2D communication.
Signal processing research deals with both 1D and 2D signals (images). This includes sparse signal processing, compressive sensing and application of machine learning to acoustic and medical signals, information retrieval and pattern recognition.
The RF stream mainly deals with front-end and antenna design for high altitude platforms and other communication subsystems, such as communication satellites.
It also deals with front-end, antenna design and other subsystems for High Altitude Platforms