We have now released the 23nd episode of the podcast Wireless Future! It has the following abstract:
For each wireless generation, we are using more bandwidth and more antennas. While the primary reason is to increase the communication capacity, it also increases the network’s ability to localize objects and sense changes in the wireless environment. The localization and sensing applications impose entirely different requirements on the desired signal and channel properties than communications. To learn more about this, Emil Björnson and Erik G. Larsson have invited Henk Wymeersch, Professor at Chalmers University of Technology, Sweden. The conversation covers the fundamentals of wireless localization, the historical evolution, and future developments that might involve machine learning, terahertz bands, and reconfigurable intelligent surfaces. Further details can be found in the articles “Collaborative sensor network localization” and “Integration of communication and sensing in 6G”.
You can watch the video podcast on YouTube:
You can listen to the audio-only podcast at the following places:
Hi Professor,
I think it would be more proper to use mmWave band to perform ISAC, since the large bandwidth can provide better resolution and accuracy. As now mmWave system usually adopts OFDM waveform where the frequency band is usually fragmented, how can we operate ISAC using OFDM waveform?
Yes, both line-of-sight communications and sensing are performing better in mmWave bands than in lower frequency bands due to the wider spectrum.
However, the fact that the range of a base station is limited to direct line-of-sight means that telecom operators have mostly been uninterested in deploying mmWave base stations, so ISAC at lower frequencies is also of interest. I don’t view ISAC as building a perfect sensing system but figuring out how one can do decent sensing inside a system deployed primarily for communications. Many papers on ISAC use discrete-time system models where OFDM has been implicitly assumed.
Thank you for your reply. I have read your paper “Multi-Static Target Detection and Power Allocation for Integrated Sensing and Communication in Cell-Free Massive MIMO”, and have this question. In terms of sensing performance, I find that you use the sensing SINR as the sensing performance metric. However, it seems that you use the multi-static sensing structure, and the sensing SINR is calculated based on the concatenated received signals from all the receivers. Is this calculation reasonable?