Millimeter wave picocellular networks: capacity analysis and system design

The explosive growth in demand for wireless mobile data, driven by the proliferationof ever more sophisticated handhelds creating and consuming rich multimedia, calls fororders of magnitude increase in the capacity of cellular data networks. Millimeter wavecommunication from picocellular base stations to mobile devices is a particularly promisingapproach for meeting this challenge because of two reasons. First, there is a largeamount of available spectrum, enabling channel bandwidths of the order of Gigahertz(GHz) which are 1-2 orders of magnitude higher than those in existing WiFi and cellularsystems at lower carrier frequencies. Second, the small carrier wavelength enables therealization of highly directive steerable arrays with a large number of antenna elements,in compact form factors, thus significantly enhancing spatial reuse. Hence, we propose toemploy the 60 GHz unlicensed band for basestation to mobile communication in outdoorpicocells.We first investigate the basic feasibility of such networks, showing that 60GHz linksare indeed viable for outdoor applications. For this purpose, we provided link budgetcalculations along with preliminary simulations which show that despite the commonconcerns about higher oxygen absorption and sensitivity to movement and blockage,picocloud architecture provides availability rate of more than 99%.Next, we explore the idea of increasing spatial reuse by shrinking picocells hopingthat interference is no longer the bottleneck given the highly directive antenna arrays atthis band. Our goal is to estimate the achievable capacity for small picocells along an urban canyon. We consider basestations with multiple faces or sectors, each with one or more antenna arrays. Each such array, termed subarray can employ Radio Frequency(RF) beamforming to communicate with one mobile user at a time. We first focus oncharacterization and modeling the inter-cell interference for one subarray on each face.Our analysis provides a strong indication of very large capacity (in the order of Tbps/km)with a few GHz of bandwidth.Following this, we explore the impact of adding multiple subarrays per face. This leadsto intra-cell interference as well as additional inter-cell interference. While the effect ofadditional inter-cell interference can be quantified within our previous framework, intracellinterference has inherently different features that call for new approaches for analysisand design. We propose a cross-layer approach to suppress the intra-cell interference intwo stages: (a) Physical layer (PHY-layer) method which mitigates interference by jointprecoding and power adaptation and (b) Medium Access Control layer (MAC-layer)method which manages the residual interference by optimizing resource allocation. Wethen estimate the capacity gain over conventional LTE cellular networks and establishthat 1000-fold capacity increase is indeed feasible via mm-wave picocellular networks.Lastly, we examine fundamental signal processing challenges associated with channelestimation and tracking for large arrays, placed within the context of system designfor a mm-wave picocellular network. Maintainance of highly directive links in the faceof blockage and mobility requires accurate estimation of the spatial channels betweenbasestation and mobile users. Here we develop the analytical framework for compressivechannel estimation and tracking. We also address the system level design discussinglink budget, overhead, and inter-cell beacon interference. Simulation results demonstratethat our compressive scheme is able to resolve mm-wave spatial channels with a relativelysmall number of compressive measurements

Sparsity-based Defense against Adversarial Attacks on Linear Classifiers

Deep neural networks represent the state of the art in machine learning in a growing number of fields, including vision, speech and natural language processing. However, recent work raises important questions about the robustness of such architectures, by showing that it is possible to induce classification errors through tiny, almost imperceptible, perturbations. Vulnerability to such "adversarial attacks", or "adversarial examples", has been conjectured to be due to the excessive linearity of deep networks. In this paper, we study this phenomenon in the setting of a linear classifier, and show that it is possible to exploit sparsity in natural data to combat $\ell_{\infty}$-bounded adversarial perturbations. Specifically, we demonstrate the efficacy of a sparsifying front end via an ensemble averaged analysis, and experimental results for the MNIST handwritten digit database. To the best of our knowledge, this is the first work to show that sparsity provides a theoretically rigorous framework for defense against adversarial attacks.Comment: Published in IEEE International Symposium on Information Theory (ISIT) 201

On the information in spike timing: neural codes derived from polychronous groups

There is growing evidence regarding the importance of spike timing in neural information processing, with even a small number of spikes carrying information, but computational models lag significantly behind those for rate coding. Experimental evidence on neuronal behavior is consistent with the dynamical and state dependent behavior provided by recurrent connections. This motivates the minimalistic abstraction investigated in this paper, aimed at providing insight into information encoding in spike timing via recurrent connections. We employ information-theoretic techniques for a simple reservoir model which encodes input spatiotemporal patterns into a sparse neural code, translating the polychronous groups introduced by Izhikevich into codewords on which we can perform standard vector operations. We show that the distance properties of the code are similar to those for (optimal) random codes. In particular, the code meets benchmarks associated with both linear classification and capacity, with the latter scaling exponentially with reservoir size

Millimeter wave picocellular networks: capacity analysis and system design

The explosive growth in demand for wireless mobile data, driven by the proliferationof ever more sophisticated handhelds creating and consuming rich multimedia, calls fororders of magnitude increase in the capacity of cellular data networks. Millimeter wavecommunication from picocellular base stations to mobile devices is a particularly promisingapproach for meeting this challenge because of two reasons. First, there is a largeamount of available spectrum, enabling channel bandwidths of the order of Gigahertz(GHz) which are 1-2 orders of magnitude higher than those in existing WiFi and cellularsystems at lower carrier frequencies. Second, the small carrier wavelength enables therealization of highly directive steerable arrays with a large number of antenna elements,in compact form factors, thus significantly enhancing spatial reuse. Hence, we propose toemploy the 60 GHz unlicensed band for basestation to mobile communication in outdoorpicocells.We first investigate the basic feasibility of such networks, showing that 60GHz linksare indeed viable for outdoor applications. For this purpose, we provided link budgetcalculations along with preliminary simulations which show that despite the commonconcerns about higher oxygen absorption and sensitivity to movement and blockage,picocloud architecture provides availability rate of more than 99%.Next, we explore the idea of increasing spatial reuse by shrinking picocells hopingthat interference is no longer the bottleneck given the highly directive antenna arrays atthis band. Our goal is to estimate the achievable capacity for small picocells along an urban canyon. We consider basestations with multiple faces or sectors, each with one or more antenna arrays. Each such array, termed subarray can employ Radio Frequency(RF) beamforming to communicate with one mobile user at a time. We first focus oncharacterization and modeling the inter-cell interference for one subarray on each face.Our analysis provides a strong indication of very large capacity (in the order of Tbps/km)with a few GHz of bandwidth.Following this, we explore the impact of adding multiple subarrays per face. This leadsto intra-cell interference as well as additional inter-cell interference. While the effect ofadditional inter-cell interference can be quantified within our previous framework, intracellinterference has inherently different features that call for new approaches for analysisand design. We propose a cross-layer approach to suppress the intra-cell interference intwo stages: (a) Physical layer (PHY-layer) method which mitigates interference by jointprecoding and power adaptation and (b) Medium Access Control layer (MAC-layer)method which manages the residual interference by optimizing resource allocation. Wethen estimate the capacity gain over conventional LTE cellular networks and establishthat 1000-fold capacity increase is indeed feasible via mm-wave picocellular networks.Lastly, we examine fundamental signal processing challenges associated with channelestimation and tracking for large arrays, placed within the context of system designfor a mm-wave picocellular network. Maintainance of highly directive links in the faceof blockage and mobility requires accurate estimation of the spatial channels betweenbasestation and mobile users. Here we develop the analytical framework for compressivechannel estimation and tracking. We also address the system level design discussinglink budget, overhead, and inter-cell beacon interference. Simulation results demonstratethat our compressive scheme is able to resolve mm-wave spatial channels with a relativelysmall number of compressive measurements