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eess.SP2024

Sparse Array Sensor Selection in ISAC with Identifiability Guarantees

Robin Rajamäki, Piya Pal

This paper investigates array geometry and waveform design for integrated sensing and communications (ISAC) employing sensor selection. We consider ISAC via index modulation, where…

eess.SP2024

Subspace Coding for Spatial Sensing

Hessam Mahdavifar, Robin Rajamäki, Piya Pal

A subspace code is defined as a collection of subspaces of an ambient vector space, where each information-encoding codeword is a subspace. This paper studies a class of spatial se…

eess.SP2024

Sparse Spatial Smoothing: Reduced Complexity and Improved Beamforming Gain via Sparse Sub-Arrays

Yinyan Bu, Robin Rajamäki, Anand Dabak +3

This paper addresses the problem of single snapshot Direction-of-Arrival (DOA) estimation, which is of great importance in a wide-range of applications including automotive radar.…

eess.SP2024

Importance of array redundancy pattern in active sensing

Robin Rajamäki, Piya Pal

This paper further investigates the role of the array geometry and redundancy in active sensing. We are interested in the fundamental question of how many point scatterers can be i…

eess.SP2024

On array geometry and self-interference in full-duplex massive MIMO communications

Robin Rajamäki, Risto Wichman

This paper studies the role of the joint transmit-receive antenna array geometry in shaping the self-interference (SI) channel in full-duplex communications. We consider a simple s…

eess.SP2024

Harnessing Holes for Spatial Smoothing with Applications in Automotive Radar

Yinyan Bu, Robin Rajamäki, Pulak Sarangi +1

This paper studies spatial smoothing using sparse arrays in single-snapshot Direction of Arrival (DOA) estimation. We consider the application of automotive MIMO radar, which tradi…