7 papers
Efficient Upper Mid-Band Spectrum Sensing with Multiple Signals
Yongjun Kim, Ali Rasteh, Sundeep Rangan +1
Spectrum sensing is a fundamental problem in the upper mid-band, where spectrum resources are shared with incumbent systems. This paper considers frequency-domain occupancy estimat…
Low-rank Preconditioning in Beamspace Domain For Massive MU-MIMO Long-Term Beamforming
Amirreza Kiani, Ali Rasteh, Marco Mezzavilla +1
Long-term beamforming substantially reduces the channel estimation and inversion overhead of conventional massive MU-MIMO receivers; yet, its construction still hinges on the inver…
Scalable Long-Term Beamforming for Massive Multi-User MIMO
Ali Rasteh, Amirreza Kiani, Marco Mezzavilla +1
Fully digital massive MIMO systems with large numbers (1000+) of antennas offer dramatically increased capacity gains from spatial multiplexing and beamforming. Designing digital r…
Interference Suppression for Massive MU-MIMO Long-Term Beamforming with Matrix Inversion Approximation
Amirreza Kiani, Ali Rasteh, Marco Mezzavilla +1
Long-term beamforming (LTBF) is a widely-used scalable alternative to instantaneous multi-user MIMO processing that leverages slowly varying spatial channel statistics. VLSI implem…
A Spatial Array for Spectrally Agile Wireless Processing
Ali Rasteh, Andrew Hennessee, Ishaan Shivhare +3
Massive MIMO is a cornerstone of next-generation wireless communication, offering significant gains in capacity, reliability, and energy efficiency. However, to meet emerging deman…
Computationally Efficient Signal Detection with Unknown Bandwidths
Ali Rasteh, Sundeep Rangan
Signal detection in environments with unknown signal bandwidth and time intervals is a fundamental problem in adversarial and spectrum-sharing scenarios. This paper addresses the p…