Problem
Research questions and friction points this paper is trying to address.
Basis Expansion Models
Channel Estimation
Pilot-Only
High-Mobility Doubly Dispersive Links
Zero Pilot-Data Interference
Exact Payload-Decoupling Conditions for Pilot-Only BEM Channel Estimation With Application to OTFS
🤖 AI Summary
本文针对高移动性双散射信道中的载荷污染问题，提出了零载荷干扰条件及导频、保护和数据布局规则，确保了基于BEM的信道估计独立于载荷。
📝 Abstract
In high-mobility doubly dispersive links, basis expansion models (BEMs) reduce channel dimensionality, yet unknown payload symbols generally contaminate conventional matched-pilot channel estimates. This paper establishes the exact conditions under which such estimates become payload-independent and derives a pilot, guard, and data-placement rule that guarantees these conditions. We prove a necessary-and-sufficient zero pilot--data interference (ZPDI) condition under which the matched-pilot least-squares (LS) solution coincides with the maximum-likelihood (ML) estimator for the reduced pilot statistic. When ZPDI holds, estimation requires a single precomputed projection. When it does not, the estimate contains a deterministic, channel-scaled payload bias that persists at high signal-to-noise ratio. A disjoint-support rule, independent of the selected basis, realizes ZPDI through pilot, guard, and data placement. We then specialize the framework to orthogonal time--frequency space (OTFS) and examine its structural and performance consequences. With the generalized complex-exponential BEM (GCE-BEM), the ZPDI estimator remains within about $2$~dB of the perfect channel state information benchmark in bit error rate at speeds up to 500~km/h.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Basis Expansion Models (BEMs)
Zero Pilot-Data Interference (ZPDI)
Orthogonal Time-Frequency Space (OTFS)
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