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 subscribe to arXiv mailings arXiv:2109.09044 ?[ pdf , other ]? cs.HC cs.DL cs.IR "Don't Downvote A\$\$\$\$\$\$s!!": An Exploration of Reddit's Advice Communities Authors: Emily Cannon , Bianca Crouse , Souvick Ghosh , Nicholas Rihn , Kristen Chua Abstract : Advice forums are a crowdsourced way to reinforce cultural norms and moral behavior. Sites like Reddit contain massive amounts of natural language human interaction, with rules and norms unique to each individual subreddit community. To explore this data, we created a dataset with top 1000 posts from each of two such forums, r/AmItheAsshole and r/relationships, and extracted natural language featu… ▽ More Advice forums are a crowdsourced way to reinforce cultural norms and moral behavior. Sites like Reddit contain massive amounts of natural language human interaction, with rules and norms unique to each individual subreddit community. To explore this data, we created a dataset with top 1000 posts from each of two such forums, r/AmItheAsshole and r/relationships, and extracted natural language features including sentiment, similarity, word frequency, and demographics using both algorithmic and manual methods. Further, we developed a method to extract demographic information from the subreddits, examined how the post authors' self-disclosures reflect the unique communities in which their posts are shared, and discussed how the authors' language use choices might be related to broader social patterns. We observed some differences between the subreddits in terms of word frequency, demographics disclosure, and gendered language. In general, both subreddits had more female posters than male, and posters tended to use more words about their opposite gender than the same. Gender-diverse posters were uncommon. Implications for future research include a more careful, inclusive focus on identity and disclosure and how that interacts with advice-seeking behavior in online communities. △ Less Submitted 18 September, 2021; originally announced September 2021. Comments: 10 pages, published at HICSS 2022 arXiv:2105.02221 ?[ pdf , other ]? cs.LG stat.ML How Fine-Tuning Allows for Effective Meta-Learning Authors: Kurtland Chua , Qi Lei , Jason D. Lee Abstract : Representation learning has been widely studied in the context of meta-learning, enabling rapid learning of new tasks through shared representations. Recent works such as MAML have explored using fine-tuning-based metrics, which measure the ease by which fine-tuning can achieve good performance, as proxies for obtaining representations. We present a theoretical framework for analyzing representati… ▽ More Representation learning has been widely studied in the context of meta-learning, enabling rapid learning of new tasks through shared representations. Recent works such as MAML have explored using fine-tuning-based metrics, which measure the ease by which fine-tuning can achieve good performance, as proxies for obtaining representations. We present a theoretical framework for analyzing representations derived from a MAML-like algorithm, assuming the available tasks use approximately the same underlying representation. We then provide risk bounds on the best predictor found by fine-tuning via gradient descent, demonstrating that the algorithm can provably leverage the shared structure. The upper bound applies to general function classes, which we demonstrate by instantiating the guarantees of our framework in the logistic regression and neural network settings. In contrast, we establish the existence of settings where any algorithm, using a representation trained with no consideration for task-specific fine-tuning, performs as well as a learner with no access to source tasks in the worst case. This separation result underscores the benefit of fine-tuning-based methods, such as MAML, over methods with "frozen representation" objectives in few-shot learning. △ Less Submitted 5 May, 2021; originally announced May 2021. arXiv:2104.01233 ?[ pdf , other ]? cs.OH cs.AI cs.LG eess.SP FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface Authors: Ravikiran Mane , Effie Chew , Karen Chua , Kai Keng Ang , Neethu Robinson , A. P. Vinod , Seong-Whan Lee , Cuntai Guan Abstract : Lack of adequate training samples and noisy high-dimensional features are key challenges faced by Motor Imagery (MI) decoding algorithms for electroencephalogram (EEG) based Brain-Computer Interface (BCI). To address these challenges, inspired from neuro-physiological signatures of MI, this paper proposes a novel Filter-Bank Convolutional Network (FBCNet) for MI classification. FBCNet employs a mu… ▽ More Lack of adequate training samples and noisy high-dimensional features are key challenges faced by Motor Imagery (MI) decoding algorithms for electroencephalogram (EEG) based Brain-Computer Interface (BCI). To address these challenges, inspired from neuro-physiological signatures of MI, this paper proposes a novel Filter-Bank Convolutional Network (FBCNet) for MI classification. FBCNet employs a multi-view data representation followed by spatial filtering to extract spectro-spatially discriminative features. This multistage approach enables efficient training of the network even when limited training data is available. More significantly, in FBCNet, we propose a novel Variance layer that effectively aggregates the EEG time-domain information. With this design, we compare FBCNet with state-of-the-art (SOTA) BCI algorithm on four MI datasets: The BCI competition IV dataset 2a (BCIC-IV-2a), the OpenBMI dataset, and two large datasets from chronic stroke patients. The results show that, by achieving 76.20% 4-class classification accuracy, FBCNet sets a new SOTA for BCIC-IV-2a dataset. On the other three datasets, FBCNet yields up to 8% higher binary classification accuracies. Additionally, using explainable AI techniques we present one of the first reports about the differences in discriminative EEG features between healthy subjects and stroke patients. Also, the FBCNet source code is available at https://github.com/ravikiran-mane/FBCNet. △ Less Submitted 17 March, 2021; originally announced April 2021. Comments: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible arXiv:2102.13651 ?[ pdf , other ]? cs.LG cs.AI cs.NE eess.SY On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning Authors: Baohe Zhang , Raghu Rajan , Luis Pineda , Nathan Lambert , André Biedenkapp , Kurtland Chua , Frank Hutter , Roberto Calandra Abstract : Model-based Reinforcement Learning (MBRL) is a promising framework for learning control in a data-efficient manner. MBRL algorithms can be fairly complex due to the separate dynamics modeling and the subsequent planning algorithm, and as a result, they often possess tens of hyperparameters and architectural choices. For this reason, MBRL typically requires significant human expertise before it can… ▽ More Model-based Reinforcement Learning (MBRL) is a promising framework for learning control in a data-efficient manner. MBRL algorithms can be fairly complex due to the separate dynamics modeling and the subsequent planning algorithm, and as a result, they often possess tens of hyperparameters and architectural choices. For this reason, MBRL typically requires significant human expertise before it can be applied to new problems and domains. To alleviate this problem, we propose to use automatic hyperparameter optimization (HPO). We demonstrate that this problem can be tackled effectively with automated HPO, which we demonstrate to yield significantly improved performance compared to human experts. In addition, we show that tuning of several MBRL hyperparameters dynamically, i.e. during the training itself, further improves the performance compared to using static hyperparameters which are kept fixed for the whole training. Finally, our experiments provide valuable insights into the effects of several hyperparameters, such as plan horizon or learning rate and their influence on the stability of training and resulting rewards. △ Less Submitted 26 February, 2021; originally announced February 2021. Comments: 19 pages, accepted by AISTATS 2021 arXiv:1805.12114 ?[ pdf , other ]? cs.LG cs.AI cs.RO stat.ML Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models Authors: Kurtland Chua , Roberto Calandra , Rowan McAllister , Sergey Levine Abstract : Model-based reinforcement learning (RL) algorithms can attain excellent sample efficiency, but often lag behind the best model-free algorithms in terms of asymptotic performance. This is especially true with high-capacity parametric function approximators, such as deep networks. In this paper, we study how to bridge this gap, by employing uncertainty-aware dynamics models. We propose a new algorit… ▽ More Model-based reinforcement learning (RL) algorithms can attain excellent sample efficiency, but often lag behind the best model-free algorithms in terms of asymptotic performance. This is especially true with high-capacity parametric function approximators, such as deep networks. In this paper, we study how to bridge this gap, by employing uncertainty-aware dynamics models. We propose a new algorithm called probabilistic ensembles with trajectory sampling (PETS) that combines uncertainty-aware deep network dynamics models with sampling-based uncertainty propagation. Our comparison to state-of-the-art model-based and model-free deep RL algorithms shows that our approach matches the asymptotic performance of model-free algorithms on several challenging benchmark tasks, while requiring significantly fewer samples (e.g., 8 and 125 times fewer samples than Soft Actor Critic and Proximal Policy Optimization respectively on the half-cheetah task). △ Less Submitted 2 November, 2018; v1 submitted 30 May, 2018; originally announced May 2018. Comments: NIPS 2018, video and code available at https://sites.google.com/view/drl-in-a-handful-of-trials/ arXiv:1805.11426 ?[ pdf ]? cs.OH Standard Cell Library Evaluation with Multiple lithography-compliant verification and Improved Synopsys Pin Access Checking Utility Authors: Yongfu Li , Wan Chia Ang , Chin Hui Lee , Kok Peng Chua , Yoong Seang Jonathan Ong , Chiu Wing Colin Hui Abstract : While standard cell layouts are drawn with minimum design rules to maximize the benefit of design area shrinkage, the complicated design rules have caused difficulties with signal routes accessing the pins in standard cell layouts. As a result, it has become a great challenge for physical layout designers to design a standard cell layout that is optimized for area, power, timing, signal integrity,… ▽ More While standard cell layouts are drawn with minimum design rules to maximize the benefit of design area shrinkage, the complicated design rules have caused difficulties with signal routes accessing the pins in standard cell layouts. As a result, it has become a great challenge for physical layout designers to design a standard cell layout that is optimized for area, power, timing, signal integrity, and printability. Multiple design iterations are required to consider pin accessibility during standard cells layout to increase the number of feasible solutions available to the router. In this work, we will demonstrate several improvements with the Synopsys PAC methodology, such as reducing the number of cells required for each Synopsys 'testcell' with the same cell abutment condition, increasing the complexity of the pin connection for better pin accessibility evaluation. We also recommend additional constraints to improve the probability of detecting pin accessibility issues. We also integrate other physical verification methods to access the design rule compliance and the printability of standard cells. We hope that the easy to use utility enables layout engineers to perform the verification, simplifying the verification methodology. △ Less Submitted 27 May, 2018; originally announced May 2018. Comments: Synopsys User Group Singapore (SNUG) 2017. arXiv admin note: substantial text overlap with arXiv:1805.10012, arXiv:1805.10745 arXiv:1805.10745 ?[ pdf ]? cs.OH Multiple-Lithography-Compliant Verification for Standard Cell Library Development Flow Authors: Yongfu Li , Wan Chia Ang , Chin Hui Lee , Kok Peng Chua , Yoong Seang Jonathan Ong , Chiu Wing Colin Hui Abstract : Starting from 22-nm, a standard cell must be designed to be full lithography-compliant, which includes Design Rule Check, Design-for-Manufacturability and Double-Patterning compliant. It has become a great challenge for physical layout designers to provide a full lithography-compliant standard cell layout that is optimized for area, power, timing, signal integrity, and yield. This challenge is fur… ▽ More Starting from 22-nm, a standard cell must be designed to be full lithography-compliant, which includes Design Rule Check, Design-for-Manufacturability and Double-Patterning compliant. It has become a great challenge for physical layout designers to provide a full lithography-compliant standard cell layout that is optimized for area, power, timing, signal integrity, and yield. This challenge is further exacerbated with abutted single- and multiple-height standard cells. At present, different foundries and library vendors have different approaches for full lithography-compliant library preparation and validation. To the best of our knowledge, there is no single tool integrates all types of lithography-compliant check in standard cell libraries validation flow. In this work, we will demonstrate multiple lithography-compliant verification for standard cell library development flow. Validation flow and detailed algorithm implementation will be explained to assist engineers to achieve full lithography-compliant standard cell libraries. An area-efficient standard cell placement methodology will also be discussed to validate the issues arises from standard cell abutment. △ Less Submitted 27 May, 2018; originally announced May 2018. Comments: Synopsys User Group Silicon Valley (SNUG) 2017 arXiv:1805.10012 ?[ pdf ]? cs.OH Constraining the Synopsys Pin Access Checker Utility for Improved Standard Cells Library Verification Flow Authors: Yongfu Li , Chin Hui Lee , Wan Chia Ang , Kok Peng Chua , Yoong Seang Jonathan Ong , Chiu Wing Colin Hui Abstract : While standard cell layouts are drawn with minimum design rules for maximum benefit of design area shrinkage, the complicated design rules begin to cause difficulties with signal routes accessing the pins in standard cell layouts. Multiple design iterations are required to resolve routing issues, thus increasing the runtime and the overall chip area. To optimize the chip performance, power and are… ▽ More While standard cell layouts are drawn with minimum design rules for maximum benefit of design area shrinkage, the complicated design rules begin to cause difficulties with signal routes accessing the pins in standard cell layouts. Multiple design iterations are required to resolve routing issues, thus increasing the runtime and the overall chip area. To optimize the chip performance, power and area (PPA) and improve the routability, it is necessary to consider the pin accessibility during standard cell development phase so that each cell is designed to maximize the number of feasible pin-access solutions available to the router. As part of the Synopsys IC Compiler Library Preparation Reference Methodology, the Synopsys Pin Access Checker (PAC) reports DRC violations associated with the standard cell. Based on Synopsys PAC's methodology, we demonstrate several methods to improve the probability of detecting pin accessibility issues, such as reducing the number of cells required for each Synopsys 'testcell', increasing the complexity of the pin connectivity assignment and recommending the router constraints. △ Less Submitted 25 May, 2018; originally announced May 2018. Journal ref: Synopsys User Conference (SNUG) Silicon Valley 2017 arXiv:1711.06276 ?[ pdf , other ]? gr-qc astro-ph.CO astro-ph.HE cs.CE doi 10.1103/PhysRevD.97.024031 Eccentric, nonspinning, inspiral, Gaussian-process merger approximant for the detection and characterization of eccentric binary black hole mergers Authors: E. A. Huerta , C. J. Moore , Prayush Kumar , Daniel George , Alvin J. K. Chua , Roland Haas , Erik Wessel , Daniel Johnson , Derek Glennon , Adam Rebei , A. Miguel Holgado , Jonathan R. Gair , Harald P. Pfeiffer Abstract : We present $\texttt{ENIGMA}$, a time domain, inspiral-merger-ringdown waveform model that describes non-spinning binary black holes systems that evolve on moderately eccentric orbits. The inspiral evolution is described using a consistent combination of post-Newtonian theory, self-force and black hole perturbation theory. Assuming eccentric binaries that circularize prior to coalescence, we smooth… ▽ More We present $\texttt{ENIGMA}$, a time domain, inspiral-merger-ringdown waveform model that describes non-spinning binary black holes systems that evolve on moderately eccentric orbits. The inspiral evolution is described using a consistent combination of post-Newtonian theory, self-force and black hole perturbation theory. Assuming eccentric binaries that circularize prior to coalescence, we smoothly match the eccentric inspiral with a stand-alone, quasi-circular merger, which is constructed using machine learning algorithms that are trained with quasi-circular numerical relativity waveforms. We show that $\texttt{ENIGMA}$ reproduces with excellent accuracy the dynamics of quasi-circular compact binaries. We validate $\texttt{ENIGMA}$ using a set of $\texttt{Einstein Toolkit}$ eccentric numerical relativity waveforms, which describe eccentric binary black hole mergers with mass-ratios between $1 \leq q \leq 5.5$, and eccentricities $e_0 \lesssim 0.2$ ten orbits before merger. We use this model to explore in detail the physics that can be extracted with moderately eccentric, non-spinning binary black hole mergers. We use $\texttt{ENIGMA}$ to show that GW150914, GW151226, GW170104, GW170814 and GW170608 can be effectively recovered with spinning, quasi-circular templates if the eccentricity of these events at a gravitational wave frequency of 10Hz satisfies $e_0\leq \{0.175,\, 0.125,\,0.175,\,0.175,\, 0.125\}$, respectively. We show that if these systems have eccentricities $e_0\sim 0.1$ at a gravitational wave frequency of 10Hz, they can be misclassified as quasi-circular binaries due to parameter space degeneracies between eccentricity and spin corrections. Using our catalog of eccentric numerical relativity simulations, we discuss the importance of including higher-order waveform multipoles in gravitational wave searches of eccentric binary black hole mergers. △ Less Submitted 24 January, 2018; v1 submitted 16 November, 2017; originally announced November 2017. Comments: 19 pages, 10 figures, 1 Appendix. v2: we use numerical relativity simulations to quantify the importance of including higher-order waveform multipoles for the detection of eccentric binary black hole mergers, references added. Accepted to Phys. Rev. D ACM Class: J.2 Journal ref: Phys. Rev. D 97, 024031 (2018) arXiv:1709.03153 ?[ pdf , other ]? cs.LG cs.AI cs.RO eess.SY MBMF: Model-Based Priors for Model-Free Reinforcement Learning Authors: Somil Bansal , Roberto Calandra , Kurtland Chua , Sergey Levine , Claire Tomlin Abstract : Reinforcement Learning is divided in two main paradigms: model-free and model-based. Each of these two paradigms has strengths and limitations, and has been successfully applied to real world domains that are appropriate to its corresponding strengths. In this paper, we present a new approach aimed at bridging the gap between these two paradigms. We aim to take the best of the two paradigms and co… ▽ More Reinforcement Learning is divided in two main paradigms: model-free and model-based. Each of these two paradigms has strengths and limitations, and has been successfully applied to real world domains that are appropriate to its corresponding strengths. In this paper, we present a new approach aimed at bridging the gap between these two paradigms. We aim to take the best of the two paradigms and combine them in an approach that is at the same time data-efficient and cost-savvy. We do so by learning a probabilistic dynamics model and leveraging it as a prior for the intertwined model-free optimization. As a result, our approach can exploit the generality and structure of the dynamics model, but is also capable of ignoring its inevitable inaccuracies, by directly incorporating the evidence provided by the direct observation of the cost. Preliminary results demonstrate that our approach outperforms purely model-based and model-free approaches, as well as the approach of simply switching from a model-based to a model-free setting. △ Less Submitted 17 October, 2017; v1 submitted 10 September, 2017; originally announced September 2017. Comments: After we submitted the paper for consideration in CoRL 2017 we found a paper published in the recent past with a similar method (see related work for a discussion). Considering the similarities between the two papers, we have decided to retract our paper from CoRL 2017 arXiv:1702.00509 ?[ pdf ]? cs.CV cs.LG Segmentation of optic disc, fovea and retinal vasculature using a single convolutional neural network Authors: Jen Hong Tan , U. Rajendra Acharya , Sulatha V. Bhandary , Kuang Chua Chua , Sobha Sivaprasad Abstract : We have developed and trained a convolutional neural network to automatically and simultaneously segment optic disc, fovea and blood vessels. Fundus images were normalised before segmentation was performed to enforce consistency in background lighting and contrast. For every effective point in the fundus image, our algorithm extracted three channels of input from the neighbourhood of the point and… ▽ More We have developed and trained a convolutional neural network to automatically and simultaneously segment optic disc, fovea and blood vessels. Fundus images were normalised before segmentation was performed to enforce consistency in background lighting and contrast. For every effective point in the fundus image, our algorithm extracted three channels of input from the neighbourhood of the point and forward the response across the 7 layer network. In average, our segmentation achieved an accuracy of 92.68 percent on the testing set from Drive database. △ Less Submitted 1 February, 2017; originally announced February 2017. arXiv:1604.00812 ?[ pdf , other ]? math.OC cs.CE Decarbonized Demand Response for Residential Plug-in Electric Vehicles in Smart Grids Authors: Farshad Rassaei , Wee-Seng Soh , Kee-Chaing Chua Abstract : Recently, in Paris, the world has reached an agreement whereby many countries commit to bolster their efforts about reducing adverse climate changes. Hence, we can expect that decarbonization will even attract more attention in different energy sectors in near future. In particular, both generation side and consumption side are required to be run more congruently and environmentally friendly. Thus… ▽ More Recently, in Paris, the world has reached an agreement whereby many countries commit to bolster their efforts about reducing adverse climate changes. Hence, we can expect that decarbonization will even attract more attention in different energy sectors in near future. In particular, both generation side and consumption side are required to be run more congruently and environmentally friendly. Thus, employing the renewables at the generation side along with our proposed decarbonized demand response (DDR) at the consumption side could significantly reduce deleterious impacts on the climate. Such ambition, at the consumption side, necessitates symbiosis and synergy between the customers and the retailer, and among customers, respectively. In other words, there should be some incentive-based collaboration between customers and the retailer as well as coordination among customers to make the objective be achieved successfully. In this paper, we present such matching demand response (DR) algorithm for residential users owning vehicle-to-grid (V2G) enabled plug-in electric vehicles (PEVs) who obtain electricity from a common retailer. The retailer itself is connected to the wholesale electricity market to purchase and sell electricity. Furthermore, we explain the details of the existing symbiosis and synergy in our system. Our simulation results illustrate that substantial cost savings can be achieved along with pollution reduction by our proposed technique. △ Less Submitted 4 April, 2016; originally announced April 2016. Comments: arXiv admin note: text overlap with arXiv:1505.06505, arXiv:1512.06600 arXiv:1408.2320 ?[ pdf , other ]? cs.CE eess.SY A Statistical Modelling and Analysis of Residential Electric Vehicles' Charging Demand in Smart Grids Authors: Farshad Rassaei , Wee-Seng Soh , Kee-Chaing Chua Abstract : Electric vehicles (EVs) add significant load on the power grid as they become widespread. The characteristics of this extra load follow the patterns of people's driving behaviours. In particular, random parameters such as arrival time and charging time of the vehicles determine their expected charging demand profile from the power grid. In this paper, we first present a model for uncoordinated cha… ▽ More Electric vehicles (EVs) add significant load on the power grid as they become widespread. The characteristics of this extra load follow the patterns of people's driving behaviours. In particular, random parameters such as arrival time and charging time of the vehicles determine their expected charging demand profile from the power grid. In this paper, we first present a model for uncoordinated charging power demand of EVs based on a stochastic process and accordingly we characterize an EV's expected daily power demand profile. Next, we illustrate it for different charging time distributions through simulations. This gives us useful insights into the long-term planning for upgrading power systems' infrastructure to accommodate EVs. Then, we incorporate departure time as another random variable into this modelling and introduce an autonomous demand response (DR) technique to manage the EVs' charging demand. Our results show that, it is possible to accommodate a large number of EVs and achieve the same peak-to-average ratio (PAR) in daily aggregated power consumption of the grid as when there is no EV in the system. This peak value can be decreased further significantly when we add vehicle-to-grid (V2G) capability in the system. △ Less Submitted 11 August, 2014; originally announced August 2014. Comments: 5 pages, 6 figures. arXiv admin note: substantial text overlap with arXiv:1407.1576 arXiv:1407.1576 ?[ pdf , other ]? cs.CE stat.AP A Statistical Modelling and Analysis of PHEVs' Power Demand in Smart Grids Authors: Farshad Rassaei , Wee-Seng Soh , Kee-Chaing Chua Abstract : Electric vehicles (EVs) and particularly plug-in hybrid electric vehicles (PHEVs) are foreseen to become popular in the near future. Not only are they much more environmentally friendly than conventional internal combustion engine (ICE) vehicles, their fuel can also be catered from diverse energy sources and resources. However, they add significant load on the power grid as they become widespread.… ▽ More Electric vehicles (EVs) and particularly plug-in hybrid electric vehicles (PHEVs) are foreseen to become popular in the near future. Not only are they much more environmentally friendly than conventional internal combustion engine (ICE) vehicles, their fuel can also be catered from diverse energy sources and resources. However, they add significant load on the power grid as they become widespread. The characteristics of this extra load follow the patterns of people's driving behaviours. In particular, random parameters such as arrival time and driven distance of the vehicles determine their expected demand profile from the power grid. In this paper, we first present a model for uncoordinated charging power demand of PHEVs based on a stochastic process and accordingly we characterize the EV's expected daily power demand profile. Next, we adopt different distributions for the EV's charging time following some available empirical research data in the literature. Simulation results show that the EV's expected daily power demand profiles obtained under the uniform, Gaussian with positive support and Rician distributions for charging time are identical when the first and second order statistics of these distributions are the same. This gives us useful insights into the long-term planning for upgrading power systems' infrastructure to accommodate PHEVs. In addition, the results from this modelling can be incorporated into designing demand response (DR) algorithms and evaluating the available DR techniques more accurately. △ Less Submitted 7 July, 2014; originally announced July 2014. Comments: 6 pages, 10 figures arXiv:1312.1450 ?[ pdf , ps , other ]? cs.IT Multi-Antenna Wireless Powered Communication with Energy Beamforming Authors: Liang Liu , Rui Zhang , Kee-Chaing Chua Abstract : The newly emerging wireless powered communication networks (WPCNs) have recently drawn significant attention, where radio signals are used to power wireless terminals for information transmission. In this paper, we study a WPCN where one multi-antenna access point (AP) coordinates energy transfer and information transfer to/from a set of single-antenna users. A harvest-then-transmit protocol is as… ▽ More The newly emerging wireless powered communication networks (WPCNs) have recently drawn significant attention, where radio signals are used to power wireless terminals for information transmission. In this paper, we study a WPCN where one multi-antenna access point (AP) coordinates energy transfer and information transfer to/from a set of single-antenna users. A harvest-then-transmit protocol is assumed where the AP first broadcasts wireless power to all users via energy beamforming in the downlink (DL), and then the users send their independent information to the AP simultaneously in the uplink (UL) using their harvested energy. To optimize the users' throughput and yet guarantee their rate fairness, we maximize the minimum throughput among all users by a joint design of the DL-UL time allocation, the DL energy beamforming, and the UL transmit power allocation plus receive beamforming. We solve this non-convex problem optimally by two steps. First, we fix the DL-UL time allocation and obtain the optimal DL energy beamforming, UL power allocation and receive beamforming to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of all users. This problem is shown to be in general non-convex; however, we convert it equivalently to a spectral radius minimization problem, which can be solved efficiently by applying the alternating optimization based on the non-negative matrix theory. Then, the optimal time allocation is found by a one-dimension search to maximize the minimum rate of all users. Furthermore, two suboptimal designs of lower complexity are proposed, and their throughput performance is compared against that of the optimal solution. △ Less Submitted 15 April, 2014; v1 submitted 5 December, 2013; originally announced December 2013. Comments: submitted for possible publication arXiv:1307.6110 ?[ pdf , ps , other ]? cs.IT doi 10.1109/TSP.2014.2303422 Secrecy Wireless Information and Power Transfer with MISO Beamforming Authors: Liang Liu , Rui Zhang , Kee-Chaing Chua Abstract : The dual use of radio signals for simultaneous wireless information and power transfer (SWIPT) has recently drawn significant attention. To meet the practical requirement that energy receivers (ERs) operate with significantly higher received power as compared to information receivers (IRs), ERs need to be deployed in more proximity to the transmitter than IRs. However, due to the broadcast nature… ▽ More The dual use of radio signals for simultaneous wireless information and power transfer (SWIPT) has recently drawn significant attention. To meet the practical requirement that energy receivers (ERs) operate with significantly higher received power as compared to information receivers (IRs), ERs need to be deployed in more proximity to the transmitter than IRs. However, due to the broadcast nature of wireless channels, one critical issue arises that the messages sent to IRs can be eavesdropped by ERs, which possess better channels from the transmitter. In this paper, we address this new secrecy communication problem in a multiuser multiple-input single-output (MISO) SWIPT system where one multi-antenna transmitter sends information and energy simultaneously to an IR and multiple ERs, each with one single antenna. To optimally design transmit beamforming vectors and their power allocation, two problems are investigated with different aims: the first problem maximizes the secrecy rate for IR subject to individual harvested energy constraints of ERs, while the second problem maximizes the weighted sum-energy transferred to ERs subject to a secrecy rate constraint for IR. We solve these two non-convex problems optimally by reformulating each of them into a two-stage problem. First, by fixing the signal-to-interference-plus-noise ratio (SINR) target for ERs (for the first problem) or IR (for the second problem), we obtain the optimal beamforming and power allocation solution by applying the technique of semidefinite relaxation (SDR). Then, the original problems are solved by a one-dimension search over the optimal SINR target for ERs or IR. Furthermore, for each of the two studied problems, suboptimal solutions of lower complexity are also proposed in which the information and energy beamforming vectors are separately designed with their power allocation. △ Less Submitted 22 January, 2014; v1 submitted 23 July, 2013; originally announced July 2013. Comments: accepted by IEEE Transactions on Signal Processing. Longer version of arXiv:1306.0969 arXiv:1306.0969 ?[ pdf , ps , other ]? cs.IT doi 10.1109/TSP.2014.2303422 Secrecy Wireless Information and Power Transfer with MISO Beamforming Authors: Liang Liu , Rui Zhang , K. C. Chua Abstract : The dual use of radio signals for simultaneous wireless information and power transfer (SWIPT) has recently drawn significant attention. To meet the practical requirement that energy receivers (ERs) operate with much higher received power than information receivers (IRs), ERs need to be deployed closer to the transmitter than IRs. However, due to the broadcast nature of wireless channels, one crit… ▽ More The dual use of radio signals for simultaneous wireless information and power transfer (SWIPT) has recently drawn significant attention. To meet the practical requirement that energy receivers (ERs) operate with much higher received power than information receivers (IRs), ERs need to be deployed closer to the transmitter than IRs. However, due to the broadcast nature of wireless channels, one critical issue is that the messages sent to IRs cannot be eavesdropped by ERs, which possess better channels from the transmitter. In this paper, we address this new secrecy communication problem in a multiuser multiple-input single-output (MISO) SWIPT system where a multi-antenna transmitter sends information and energy simultaneously to one IR and multiple ERs, each with a single antenna. By optimizing transmit beamforming vectors and their power allocation, we maximize the weighted sum-energy transferred to ERs subject to a secrecy rate constraint for the information sent to the IR. We solve this non-convex problem optimally by reformulating it into a two-stage problem. First, we fix the signal-to-interference-plus-noise ratio (SINR) at the IR and obtain the optimal beamforming solution by applying the technique of semidefinite relaxation (SDR). Then the original problem is solved by a one-dimension search over the optimal SINR value for the IR. Furthermore, two suboptimal low-complexity beamforming schemes are proposed, and their achievable (secrecy) rate-energy (R-E) regions are compared against that by the optimal scheme. △ Less Submitted 30 July, 2013; v1 submitted 4 June, 2013; originally announced June 2013. Comments: accepted by the IEEE Global Communications Conference 2013 arXiv:1302.0585 ?[ pdf , ps , other ]? cs.IT doi 10.1109/TCOMM.2013.071813.130105 Wireless Information and Power Transfer: A Dynamic Power Splitting Approach Authors: Liang Liu , Rui Zhang , Kee-Chaing Chua Abstract : Scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the flat-fading channel, where the receiver replenishes energy via WEH from the signals sent by the transmitter. We consider a SISO (single-input single-output) system where the single-antenna receiver cannot… ▽ More Scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the flat-fading channel, where the receiver replenishes energy via WEH from the signals sent by the transmitter. We consider a SISO (single-input single-output) system where the single-antenna receiver cannot decode information and harvest energy independently from the same signal received. Under this practical constraint, we propose a dynamic power splitting (DPS) scheme, where the received signal is split into two streams with adjustable power levels for information decoding and energy harvesting separately based on the instantaneous channel condition that is assumed to be known at the receiver. We derive the optimal power splitting rule at the receiver to achieve various trade-offs between the maximum ergodic capacity for information transfer and the maximum average harvested energy for power transfer. Moreover, for the case when the channel state information is also known at the transmitter, we investigate the joint optimization of transmitter power control and receiver power splitting. Finally, we extend the result for DPS to the SIMO (single-input multiple-output) system and investigate a low-complexity power splitting scheme termed antenna switching. △ Less Submitted 30 June, 2013; v1 submitted 4 February, 2013; originally announced February 2013. Comments: accepted by IEEE Transactions on Communication arXiv:1212.5352 ?[ pdf ]? cs.CV On the Adaptability of Neural Network Image Super-Resolution Authors: Kah Keong Chua , Yong Haur Tay Abstract : In this paper, we described and developed a framework for Multilayer Perceptron (MLP) to work on low level image processing, where MLP will be used to perform image super-resolution. Meanwhile, MLP are trained with different types of images from various categories, hence analyse the behaviour and performance of the neural network. The tests are carried out using qualitative test, in which Mean Squ… ▽ More In this paper, we described and developed a framework for Multilayer Perceptron (MLP) to work on low level image processing, where MLP will be used to perform image super-resolution. Meanwhile, MLP are trained with different types of images from various categories, hence analyse the behaviour and performance of the neural network. The tests are carried out using qualitative test, in which Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). The results showed that MLP trained with single image category can perform reasonably well compared to methods proposed by other researchers. △ Less Submitted 21 December, 2012; originally announced December 2012. Comments: Image Super Resolution, Neural Network, Multilayer Perceptron, Mean Squared Error, Peak Signal-to-Noise Ratio, Structural Similarity Index arXiv:1204.2035 ?[ pdf , ps , other ]? cs.IT Wireless Information Transfer with Opportunistic Energy Harvesting Authors: Liang Liu , Rui Zhang , Kee-Chaing Chua Abstract : Energy harvesting is a promising solution to prolong the operation of energy-constrained wireless networks. In particular, scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the narrowband flat-fading channel subject to time-varying co-channel interference. I… ▽ More Energy harvesting is a promising solution to prolong the operation of energy-constrained wireless networks. In particular, scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the narrowband flat-fading channel subject to time-varying co-channel interference. It is assumed that the receiver has no fixed power supplies and thus needs to replenish energy opportunistically via WEH from the unintended interference and/or the intended signal sent by the transmitter. We further assume a single-antenna receiver that can only decode information or harvest energy at any time due to the practical circuit limitation. Therefore, it is important to investigate when the receiver should switch between the two modes of information decoding (ID) and energy harvesting (EH), based on the instantaneous channel and interference condition. In this paper, we derive the optimal mode switching rule at the receiver to achieve various trade-offs between wireless information transfer and energy harvesting. Specifically, we determine the minimum transmission outage probability for delay-limited information transfer and the maximum ergodic capacity for no-delay-limited information transfer versus the maximum average energy harvested at the receiver, which are characterized by the boundary of so-called "outage-energy" region and "rate-energy" region, respectively. Moreover, for the case when the channel state information (CSI) is known at the transmitter, we investigate the joint optimization of transmit power control, information and energy transfer scheduling, and the receiver's mode switching. Our results provide useful guidelines for the efficient design of emerging wireless communication systems powered by opportunistic WEH. △ Less Submitted 31 October, 2012; v1 submitted 9 April, 2012; originally announced April 2012. Comments: to appear in IEEE Transactions on Wireless Communication arXiv:1202.2231 ?[ pdf , ps , other ]? cs.IT doi 10.1109/TWC.2012.031212.111585 Achieving Global Optimality for Weighted Sum-Rate Maximization in the K-User Gaussian Interference Channel with Multiple Antennas Authors: Liang Liu , Rui Zhang , Kee-Chaing Chua Abstract : Characterizing the global maximum of weighted sum-rate (WSR) for the K-user Gaussian interference channel (GIC), with the interference treated as Gaussian noise, is a key problem in wireless communication. However, due to the users' mutual interference, this problem is in general non-convex and thus cannot be solved directly by conventional convex optimization techniques. In this paper, by jointly… ▽ More Characterizing the global maximum of weighted sum-rate (WSR) for the K-user Gaussian interference channel (GIC), with the interference treated as Gaussian noise, is a key problem in wireless communication. However, due to the users' mutual interference, this problem is in general non-convex and thus cannot be solved directly by conventional convex optimization techniques. In this paper, by jointly utilizing the monotonic optimization and rate profile techniques, we develop a new framework to obtain the globally optimal power control and/or beamforming solutions to the WSR maximization problems for the GICs with single-antenna transmitters and single-antenna receivers (SISO), single-antenna transmitters and multi-antenna receivers (SIMO), or multi-antenna transmitters and single-antenna receivers (MISO). Different from prior work, this paper proposes to maximize the WSR in the achievable rate region of the GIC directly by exploiting the facts that the achievable rate region is a "normal" set and the users' WSR is a "strictly increasing" function over the rate region. Consequently, the WSR maximization is shown to be in the form of monotonic optimization over a normal set and thus can be solved globally optimally by the existing outer polyblock approximation algorithm. However, an essential step in the algorithm hinges on how to efficiently characterize the intersection point on the Pareto boundary of the achievable rate region with any prescribed "rate profile" vector. This paper shows that such a problem can be transformed into a sequence of signal-to-interference-plus-noise ratio (SINR) feasibility problems, which can be solved efficiently by existing techniques. Numerical results validate that the proposed algorithms can achieve the global WSR maximum for the SISO, SIMO or MISO GIC. △ Less Submitted 10 February, 2012; originally announced February 2012. Comments: This is the longer version of a paper to appear in IEEE Transactions on Wireless Communications . From：
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