Abstract-Compressed Sensing aims to capture attributes of k-sparse signals using very few measurements. In the standard Compressed Sensing paradigm, the N × C measurement matrix Φ is required to act as a near isometry on the set of all k-sparse signals (Restricted Isometry Property or RIP). If Φ satisfies the RIP, then Basis Pursuit or Matching Pursuit recovery algorithms can be used to recover any k-sparse vector α from the N measurements Φα. Although it is known that certain probabilistic processes generate N × C matrices that satisfy RIP with high probability, there is no practical algorithm for verifying whether a given sensing matrix Φ has this property, crucial for the feasibility of the standard recovery algorithms. In contrast this paper provides simple criteria that guarantee that a deterministic sensing matrix satisfying these criteria acts as a near isometry on an overwhelming majority of k-sparse signals; in particular, most such signals have a unique representation in the measurement domain. Probability still plays a critical role, but it enters the signal model rather than the construction of the sensing matrix. An essential element in our construction is that we require the columns of the sensing matrix to form a group under pointwise multiplication. The construction allows recovery methods for which the expected performance is sublinear in C, and only quadratic in N , as compared to the superlinear complexity in C of the Basis Pursuit or Matching Pursuit algorithms; the focus on expected performance is more typical of mainstream signal processing than the worst-case analysis that prevails in standard Compressed Sensing. Our framework encompasses many families of deterministic sensing matrices, including those formed from discrete chirps, Delsarte-Goethals codes, and extended BCH codes.

No abstract

No abstract

We present a systematic way of constructing a Doppler resilient sequence of Golay complementary waveforms for radar, for which the composite ambiguity function maintains ideal shape at small Doppler shifts. The idea is to determine a sequence of Golay pairs that annihilates the low-order terms of the Taylor expansion of the composite ambiguity function. The Prouhet-Thue-Morse sequence plays a key role in the construction of Doppler resilient sequences of Golay pairs. We extend this construction to multiple dimensions. In particular, we consider radar polarimetry, where the dimensions are realized by two orthogonal polarizations. We determine a sequence of two-by-two Alamouti matrices, where the entries involve Golay pairs and for which the matrix-valued composite ambiguity function vanishes at small Doppler shifts.

A wideband space-time channel model is defined, which captures the multiple dependencies and variability in multicell system-wide operating environments. The model provides a unified treatment of spatial and temporal parameters, giving their statistical description and dependencies across a large geographical area for three outdoor environments pertinent to third-generation cellular system simulations. Parameter values are drawn from a broad base of recently published wideband and multiple-antenna measurements. A methodology is given to generate fast-fading coefficients between a base station and a mobile user based on the summation of directional plane waves derived from the statistics of the space-time parameters. Extensions to the baseline channel model, such as polarized antennas, are given to provide a greater variety of spatial environments. Despite its comprehensive nature, the model's implementation complexity is reasonable so it can be used in simulating large-scale systems. Output statistics and capabilities are used to illustrate the main characteristics of the model. IEEE Transactions on Vehicular TechnologyThis work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Abstract-A wideband space-time channel model is defined, which captures the multiple dependencies and variability in multicell system-wide operating environments. The model provides a unified treatment of spatial and temporal parameters, giving their statistical description and dependencies across a large geographical area for three outdoor environments pertinent to thirdgeneration cellular system simulations. Parameter values are drawn from a broad base of recently published wideband and multiple-antenna measurements. A methodology is given to generate fast-fading coefficients between a base station and a mobile user based on the summation of directional plane waves derived from the statistics of the space-time parameters. Extensions to the baseline channel model, such as polarized antennas, are given to provide a greater variety of spatial environments. Despite its comprehensive nature, the model's implementation complexity is reasonable so it can be used in simulating large-scale systems. Output statistics and capacities are used to illustrate the main characteristics of the model.