8 papers
Quantum-Native Maximum Likelihood Detection in Random Access Channel with Overloaded MIMO
Hyoga Iizumi, Naoki Ishikawa, Shunsuke Uehashi +3
In this paper, we propose a quantum-native formulation of maximum likelihood detection (MLD) for overloaded multiple-input multiple-output (MIMO) systems in a random access channel…
Z-Opt: A Near-Optimal Reduced-Complexity Two-Dimensional Grassmannian Constellation
Kotaro Shigenaga, Hiroki Iimori, Yuto Hama +3
Grassmannian constellations are known to achieve the capacity of noncoherent communications over Rayleigh fading channels in the high-SNR regime, yet their efficient construction r…
Sparsification of Precoding Codebooks for PAPR Reduction via Grassmannian Representations
Joe Asano, Yuto Hama, Hiroki Iimori +2
In this letter, we propose a sparsification method for precoding codebooks that reduces the peak-to-average power ratio (PAPR) while preserving the achievable rate. By exploiting t…
Low-Complexity and Power-Efficient Precoding Codebook Design on Sparse Grassmannian
Joe Asano, Yuto Hama, Hiroki Iimori +3
We propose a sparse Grassmannian design for precoding codebooks. Due to their sparse structure, our proposed codebooks achieve low peak-to-average power ratio (PAPR), low complexit…
Superimposed Pilot-Based OTFS: Will It Work?
Yuta Kanazawa, Hiroki Iimori, Chandan Pradhan +2
Orthogonal time frequency space (OTFS) modulation is a promising solution to handle doubly-selective fading, but its channel estimation is a nontrivial task in terms of maximizing…
Sparse Grassmannian Design for Noncoherent Codes via Schubert Cell Decomposition
Joe Asano, Yuto Hama, Hiroki Iimori +3
In this paper, we propose a method for designing sparse Grassmannian codes for noncoherent multiple-input multiple-output systems. Conventional pairwise error probability formulati…