8 papers
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…
Repeater-Assisted MIMO Can Also Boost Frequency Diversity: A Semi-Analytic Study
Hiroki Iimori, Yuto Hama
Massive multiple-input multiple-output (MIMO) has enabled substantial spatial multiplexing and array gains in real-world systems, while distributed MIMO (D-MIMO) improves macro-div…
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…
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…
Joint Pilot Allocation and Sequence Design for MIMO-OFDM Systems With Channel Sparsity
Kabuto Arai, Koji Ishibashi, Hiroki Iimori +3
This paper proposes a joint optimization of pilot subcarrier allocation and non-orthogonal sequence for multiple-input-multiple-output (MIMO)-orthogonal frequency-division multiple…
Maximizing Spectrum Efficiency of Data-Carrying Reference Signals via Bayesian Optimization
Taiki Kato, Hiroki Iimori, Chandan Pradhan +2
Data-carrying reference signals are a type of reference signal (RS) constructed on the Grassmann manifold, which allows for simultaneous data transmission and channel estimation to…