Compressed Sensing-Aided Multi-Dimensional Index Modulation
نویسندگان
چکیده
منابع مشابه
Multi-Dimensional Wireless Tomography Using Tensor-Based Compressed Sensing
Wireless tomography is a technique for inferring a physical environment within a monitored region by analyzing RF signals traversed across the region. In this paper, we consider wireless tomography in a two and higher dimensionally structured monitored region, and propose a multi-dimensional wireless tomography scheme based on compressed sensing to estimate a spatial distribution of shadowing l...
متن کاملThree-Dimensional Compressed Sensing for Dynamic MRI
Introduction: Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is a valuable tool used in a number of clinical applications. However, imaging of time-varying objects is a challenging task when both high spatial resolution and high temporal resolution is desired. It has been demonstrated that radial imaging techniques can yield increased temporal resolution without sacrificing sp...
متن کاملInfinite dimensional compressed sensing from anisotropic measurements
In this paper, we consider a compressed sensing problem in which both the measurement and the sparsifying systems are assumed to be frames (not necessarily tight) of the underlying Hilbert space of signals, which may be finite or infinite dimensional. The main result gives explicit bounds on the number of measurements in order to achieve stable recovery, which depends on the mutual coherence of...
متن کاملInfinite-dimensional compressed sensing and function interpolation
We introduce and analyze a framework for function interpolation using compressed sensing. This framework – which is based on weighted l minimization – does not require a priori bounds on the expansion tail in either its implementation or its theoretical guarantees. Moreover, in the absence of noise it leads to genuinely interpolatory approximations. We also establish a series of new recovery gu...
متن کاملGeneralized Sampling and Infinite-Dimensional Compressed Sensing
We introduce and analyze an abstract framework, and corresponding method, for compressed sensing in infinite dimensions. This extends the existing theory from signals in finite-dimensional vectors spaces to the case of separable Hilbert spaces. We explain why such a new theory is necessary, and demonstrate that existing finite-dimensional techniques are ill-suited for solving a number of import...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Communications
سال: 2019
ISSN: 0090-6778,1558-0857
DOI: 10.1109/tcomm.2019.2902393