Spectrum Sharing between Cooperative Relay and Ad-hoc Networks: Dynamic Transmissions under Computation and Signaling Limitations

This paper studies a spectrum sharing scenario between a cooperative relay network (CRN) and a nearby ad-hoc network. In particular, we consider a dynamic spectrum access and resource allocation problem of the CRN. Based on sensing and predicting the ad-hoc transmission behaviors, the ergodic traffic collision time between the CRN and ad-hoc network is minimized subject to an ergodic uplink throughput requirement for the CRN. We focus on real-time implementation of spectrum sharing policy under practical computation and signaling limitations. In our spectrum sharing policy, most computation tasks are accomplished off-line. Hence, little real-time calculation is required which fits the requirement of practical applications. Moreover, the signaling procedure and computation process are designed carefully to reduce the time delay between spectrum sensing and data transmission, which is crucial for enhancing the accuracy of traffic prediction and improving the performance of interference mitigation. The benefits of spectrum sensing and cooperative relay techniques are demonstrated by our numerical experiments.Comment: 5 pages, 3 figures, to appear in IEEE International Conference on Communications (ICC 2011

Optimal Distributed Resource Allocation for Decode-and-Forward Relay Networks

This paper presents a distributed resource allocation algorithm to jointly optimize the power allocation, channel allocation and relay selection for decode-and-forward (DF) relay networks with a large number of sources, relays, and destinations. The well-known dual decomposition technique cannot directly be applied to resolve this problem, because the achievable data rate of DF relaying is not strictly concave, and thus the local resource allocation subproblem may have non-unique solutions. We resolve this non-strict concavity problem by using the idea of the proximal point method, which adds quadratic terms to make the objective function strictly concave. However, the proximal solution adds an extra layer of iterations over typical duality based approaches, which can significantly slow down the speed of convergence. To address this key weakness, we devise a fast algorithm without the need for this additional layer of iterations, which converges to the optimal solution. Our algorithm only needs local information exchange, and can easily adapt to variations of network size and topology. We prove that our distributed resource allocation algorithm converges to the optimal solution. A channel resource adjustment method is further developed to provide more channel resources to the bottleneck links and realize traffic load balance. Numerical results are provided to illustrate the benefits of our algorithm

Optimal Real-time Spectrum Sharing between Cooperative Relay and Ad-hoc Networks

Optimization based spectrum sharing strategies have been widely studied. However, these strategies usually require a great amount of real-time computation and significant signaling delay, and thus are hard to be fulfilled in practical scenarios. This paper investigates optimal real-time spectrum sharing between a cooperative relay network (CRN) and a nearby ad-hoc network. Specifically, we optimize the spectrum access and resource allocation strategies of the CRN so that the average traffic collision time between the two networks can be minimized while maintaining a required throughput for the CRN. The development is first for a frame-level setting, and then is extended to an ergodic setting. For the latter setting, we propose an appealing optimal real-time spectrum sharing strategy via Lagrangian dual optimization. The proposed method only involves a small amount of real-time computation and negligible control delay, and thus is suitable for practical implementations. Simulation results are presented to demonstrate the efficiency of the proposed strategies.Comment: One typo in the caption of Figure 5 is correcte

Generation of Intense High-Order Vortex Harmonics

This paper presents the method for the first time to generate intense high-order optical vortices that carry orbital angular momentum in the extreme ultraviolet region. In three-dimensional particle-in-cell simulation, both the reflected and transmitted light beams include high-order harmonics of the Laguerre-Gaussian (LG) mode when a linearly polarized LG laser pulse impinges on a solid foil. The mode of the generated LG harmonic scales with its order, in good agreement with our theoretical analysis. The intensity of the generated high-order vortex harmonics is close to the relativistic region, and the pulse duration can be in attosecond scale. The obtained intense vortex beam possesses the combined properties of fine transversal structure due to the high-order mode and the fine longitudinal structure due to the short wavelength of the high-order harmonics. Thus, the obtained intense vortex beam may have extraordinarily promising applications for high-capacity quantum information and for high-resolution detection in both spatial and temporal scales because of the addition of a new degree of freedom

Analysis of coupling between two sub-machines in co-axis dual-mechanical-port flux-switching PM machine for fuel-based extended range electric vehicles

The permanent magnet (PM) field coupling between inner and outer machines of co-axis dual-mechanical-port flux-switching PM (CADMP-FSPM) machines is investigated. Firstly, the relationships between the inner and outer stator teeth are analytically evaluated, with three key stator teeth types defined, i.e. series, parallel, and independent teeth. Secondly, the negative effects of PM field coupling, including high even-order electromotive force (EMF) harmonics, three-phase EMFs asymmetry and DC bias component in flux-linkages, are investigated and verified by two CADMP-FSPM machines, namely, 5/6–12/22, and 5/6–18/42 structures. It is found that for avoiding the negative effects of PM field coupling, all inner and outer stator teeth types should be the same, thus, a 10/12–12/22 structure CADMP-FSPM machine is introduced for analysis. Thirdly, the performance of the 10/12–12/22, 5/6–12/22, and 5/6–18/42 structures, featured by PM field distributions, d-axis flux-linkage ripples, cogging torques, electromagnetic torques, losses and efficiencies, are comparatively analysed by finite element (FE) analysis. The results indicate that the 10/12–12/22 structure exhibits the lowest PM field coupling level and the best performance. Moreover, the 10/12–12/22 structure can avoid all the negative effects of PM field couplings. A prototyped 10/12–12/22 CADMP-FSPM machine is built and tested to verify the FE predicted results.</p

AutoDiff: combining Auto-encoder and Diffusion model for tabular data synthesizing

Diffusion model has become a main paradigm for synthetic data generation in many subfields of modern machine learning, including computer vision, language model, or speech synthesis. In this paper, we leverage the power of diffusion model for generating synthetic tabular data. The heterogeneous features in tabular data have been main obstacles in tabular data synthesis, and we tackle this problem by employing the auto-encoder architecture. When compared with the state-of-the-art tabular synthesizers, the resulting synthetic tables from our model show nice statistical fidelities to the real data, and perform well in downstream tasks for machine learning utilities. We conducted the experiments over $15$ publicly available datasets. Notably, our model adeptly captures the correlations among features, which has been a long-standing challenge in tabular data synthesis. Our code is available at https://github.com/UCLA-Trustworthy-AI-Lab/AutoDiffusion

単面葉における形態形成鍵遺伝子の発現パターンと細胞分裂パターンとの比較解析

学位の種別: 課程博士審査委員会委員 : （主査）東京大学准教授 杉山 宗隆, 東京大学教授 平野 博之, 東京大学准教授 阿部 光知, 東京大学准教授 伊藤 純一, 東京大学教授 塚谷 裕一University of Tokyo(東京大学