Low Complexity Noncoherent Iterative Detector for Continuous Phase Modulation Systems

This paper focuses on the noncoherent iterative detection of continuous phase modulation. A class of simplified receivers based on Principal-Component-Analysis (PCA) and Exponential-Window (EW) is developed. The proposed receiver is evaluated in terms of minimum achievable Euclidean distance, simulated bit error rate and achievable capacity. The performance of the proposed receiver is discussed in the context of mismatched receiver and the equivalent Euclidean distance is derived. Analysis and numerical results reveal that the proposed algorithm can approach the coherent performance and outperforms existing algorithm in terms of complexity and performance. It is shown that the proposed receiver can significantly reduce the detection complexity while the performance is comparable with existing algorithms

MMSE-optimal approximation of continuous-phase modulated signal as superposition of linearly modulated pulses

The optimal linear modulation approximation of any M-ary continuous-phase modulated (CPM) signal under the minimum mean-square error (MMSE) criterion is presented in this paper. With the introduction of the MMSE signal component, an M-ary CPM signal is exactly represented as the superposition of a finite number of MMSE incremental pulses, resulting in the novel switched linear modulation CPM signal models. Then, the MMSE incremental pulse is further decomposed into a finite number of MMSE pulse-amplitude modulated (PAM) pulses, so that an M-ary CPM signal is alternatively expressed as the superposition of a finite number of MMSE PAM components, similar to the Laurent representation. Advantageously, these MMSE PAM components are mutually independent for any modulation index. The optimal CPM signal approximation using lower order MMSE incremental pulses, or alternatively, using a small number of MMSE PAM pulses, is also made possible, since the approximation error is minimized in the MMSE sense. Finally, examples of the MMSE-optimal CPM signal approximation and its comparison with the Laurent approximation approach are given using raised-cosine frequency-pulse CPM schemes

Design of Simplified Maximum-Likelihood Receivers for Multiuser CPM Systems

A class of simplified maximum-likelihood receivers designed for continuous phase modulation based multiuser systems is proposed. The presented receiver is built upon a front end employing mismatched filters and a maximum-likelihood detector defined in a low-dimensional signal space. The performance of the proposed receivers is analyzed and compared to some existing receivers. Some schemes are designed to implement the proposed receivers and to reveal the roles of different system parameters. Analysis and numerical results show that the proposed receivers can approach the optimum multiuser receivers with significantly (even exponentially in some cases) reduced complexity and marginal performance degradation

Lorenz gauge gravitational self-force calculations of eccentric binaries using a frequency domain procedure

We present an algorithm for calculating the metric perturbations and gravitational self-force for extreme-mass-ratio inspirals (EMRIs) with eccentric orbits. The massive black hole is taken to be Schwarzschild and metric perturbations are computed in Lorenz gauge. The perturbation equations are solved as coupled systems of ordinary differential equations in the frequency domain. Accurate local behavior of the metric is attained through use of the method of extended homogeneous solutions and mode-sum regularization is used to find the self-force. We focus on calculating the self-force with sufficient accuracy to ensure its error contributions to the phase in a long term orbital evolution will be $\delta\Phi \lesssim 10^{-2}$ radians. This requires the orbit-averaged force to have fractional errors $\lesssim 10^{-8}$ and the oscillatory part of the self-force to have errors $\lesssim 10^{-3}$ (a level frequently easily exceeded). Our code meets this error requirement in the oscillatory part, extending the reach to EMRIs with eccentricities of $e \lesssim 0.8$, if augmented by use of fluxes for the orbit-averaged force, or to eccentricities of $e \lesssim 0.5$ when used as a stand-alone code. Further, we demonstrate accurate calculations up to orbital separations of $a \simeq 100 M$, beyond that required for EMRI models and useful for comparison with post-Newtonian theory. Our principal developments include (1) use of fully constrained field equations, (2) discovery of analytic solutions for even-parity static modes, (3) finding a pre-conditioning technique for outer homogeneous solutions, (4) adaptive use of quad-precision and (5) jump conditions to handle near-static modes, and (6) a hybrid scheme for high eccentricities

Active Tactile Sensing for Texture Perception in Robotic Systems

This thesis presents a comprehensive study of tactile sensing, particularly on the prob- lem of active texture perception. It includes a brief introduction to tactile sensing technology and the neural basis for tactile perception. It follows the literature review of textural percep- tion with tactile sensing. I propose a decoding and perception pipeline to tackle fine-texture classification/identification problems via active touching. Experiments are conducted using a 7DOF robotic arm with a finger-shaped tactile sensor mounted on the end-effector to per- form sliding/rubbing movements on multiple fabrics. Low-dimensional frequency features are extracted from the raw signals to form a perceptive feature space, where tactile signals are mapped and segregated into fabric classes. Fabric classes can be parameterized and sim- plified in the feature space using elliptical equations. Results from experiments of varied control parameters are compared and visualized to show that different exploratory move- ments have an apparent impact on the perceived tactile information. It implies the possibil- ity of optimising the robotic movements to improve the textural classification/identification performance