12 papers · 1 filter
CRB-Optimal Arrays and Waveforms in Active Sensing: Role of Redundancy and Spatial Covariance of Array Geometry
Ids van der Werf, Robin Rajamäki, Geert Leus
This paper characterizes the performance limits of optimal array designs using orthogonal and coherent waveforms for both linear and planar arrays. For orthogonal waveforms, we sho…
Grassmannian-Coded Beamforming for mmWave Channel Sensing with Unknown Complex Path Gain
Parthasarathi Khirwadkar, Robin Rajamäki, Piya Pal
This paper introduces a subspace-coding perspective to millimeter-wave channel sensing with a single RF chain when the complex channel gain is unknown. We show that in this case, c…
Beyond-Diagonal RIS: Adversarial Channels and Optimality of Low-Complexity Architectures
Atso Iivanainen, Robin Rajamäki, Visa Koivunen
Beyond-diagonal reconfigurable intelligent surfaces (BD-RISs) have recently gained attention as an enhancement to conventional RISs. BD-RISs allow optimizing not only the phase, bu…
Generative Deep Synthesis of MIMO Sensing Waveforms with Desired Transmit Beampattern
Vesa Saarinen, Robin Rajamäki, Visa Koivunen
This paper develops a generative deep learning model for the synthesis of multiple-input multiple-output (MIMO) active sensing waveforms with desired properties, including constant…
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…
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.…