arXiv subjects

Shivendra S. Panwar

Publications and source records attributed to Shivendra S. Panwar.

16 recordsLinked to original sources

arXiv2023

Can 5G NR Sidelink communications support wireless augmented reality?

Smart glasses that support augmented reality (AR) have the potential to become the consumer's primary medium of connecting to the future internet. For the best quality of user experience, AR glasses must have a small form factor and long battery life, while satisfying the data rate and latency requirements of AR applications. To extend the AR glasses' battery life, the computation and processing involved in AR may be offloaded to a companion device, such as a smartphone, through a wireless connection. Sidelink (SL), i.e., the D2D communication interface of 5G NR, is a potential candidate for this wireless link. In this paper, we use system-level simulations to analyze the feasibility of NR SL for supporting AR. Our simulator incorporates the PHY layer structure and MAC layer resource scheduling of 3GPP SL, standard 3GPP channel models, and MCS configurations. Our results suggest that the current SL standard specifications are insufficient for high-end AR use cases with heavy interaction but can support simpler previews and file transfers. We further propose two enhancements to SL resource allocation, which have the potential to offer significant performance improvements for AR applications.

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arXiv2021

Full-Duplex Cell-Free mMIMO Systems: Analysis and Decentralized Optimization

Cell-free (CF) massive multiple-input-multiple-output (mMIMO) deployments are usually investigated with half-duplex nodes and high-capacity fronthaul links. To leverage the possible gains in throughput and energy efficiency (EE) of full-duplex (FD) communications, we consider a FD CF mMIMO system with practical limited-capacity fronthaul links. We derive closed-form spectral efficiency (SE) lower bounds for this system with maximum-ratio combining/maximum-ratio transmission processing and optimal uniform quantization. We then optimize the weighted sum EE (WSEE) via downlink and uplink power control by using a two-layered approach: the first layer formulates the optimization as a generalized convex program, while the {second layer} solves the optimization decentrally using the alternating direction method of multipliers. We analytically show that the proposed two-layered formulation yields a Karush-Kuhn-Tucker point of the original WSEE optimization. We numerically show the influence of weights on the individual EE of the users, which demonstrates the utility of the WSEE metric to incorporate heterogeneous EE requirements of users. We show that low fronthaul capacity reduces the number of users each AP can support, and the cell-free system, consequently, becomes user-centric.

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arXiv2021

FD Cell-Free mMIMO: Analysis and Optimization

Cell-free (CF) massive multiple-input-multiple-output (mMIMO) deployments are usually investigated with half-duplex nodes and high-capacity fronthaul links. To leverage the possible gains in throughput and energy efficiency (EE) of full-duplex (FD) communications, we consider a FD CF mMIMO system with practical limited-capacity fronthaul links. We derive closed-form spectral efficiency (SE) lower bounds for this system with maximum-ratio combining/maximum-ratio transmission processing and optimal uniform quantization. We then optimize the weighted sum EE (WSEE) via downlink and uplink power control by using a {two-layered} approach: the first layer formulates the optimization as a generalized convex program, while the second layer solves the optimization decentrally using alternating direction method of multipliers. We analytically show that the proposed two-layered formulation yields a Karush-Kuhn-Tucker point of the original WSEE optimization. We numerically show the influence of weights on the individual EE of the users, which demonstrates the utility of WSEE metric to incorporate heterogeneous EE requirements of users. We show that the low fronthaul capacity reduces the number of users each AP can support, and the cell-free system, consequently, becomes user-centric.

eess.SP↗

arXiv2020

Tomography Based Learning for Load Distribution through Opaque Networks

Applications such as virtual reality and online gaming require low delays for acceptable user experience. A key task for over-the-top (OTT) service providers who provide these applications is sending traffic through the networks to minimize delays. OTT traffic is typically generated from multiple data centers which are multi-homed to several network ingresses. However, information about the path characteristics of the underlying network from the ingresses to destinations is not explicitly available to OTT services. These can only be inferred from external probing. In this paper, we combine network tomography with machine learning to minimize delays. We consider this problem in a general setting where traffic sources can choose a set of ingresses through which their traffic enter a black box network. The problem in this setting can be viewed as a reinforcement learning problem with constraints on a continuous action space, which to the best of our knowledge have not been investigated by the machine learning community. Key technical challenges to solving this problem include the high dimensionality of the problem and handling constraints that are intrinsic to networks. Evaluation results show that our methods achieve up to 60% delay reductions in comparison to standard heuristics. Moreover, the methods we develop can be used in a centralized manner or in a distributed manner by multiple independent agents.

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arXiv2018

Realtime Scheduling and Power Allocation Using Deep Neural Networks

With the increasing number of base stations (BSs) and network densification in 5G, interference management using link scheduling and power control are vital for better utilization of radio resources. However, the complexity of solving link scheduling and the power control problem grows exponentially with the number of BS. Due to high computation time, previous methods are useful for research purposes but impractical for real time usage. In this paper we propose to use deep neural networks (DNNs) to approximate optimal link scheduling and power control for the case with multiple small cells. A deep Q-network (DQN) estimates a suitable schedule, then a DNN allocates power for the corresponding schedule. Simulation results show that the proposed method achieves over five orders of magnitude speed-up with less than nine percent performance loss, making real time usage practical.

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arXiv2018

Capacity Analysis for Full Duplex Self-backhauled Small Cells

Full duplex (FD) communication enables simultaneous transmission and reception on the same frequency band. Though it has the potential of doubling the throughput on isolated links, in reality, higher interference and asymmetric traffic demands in the uplink and downlink could significantly reduce the gains of FD operations. In this paper, we consider the application of FD operation in self-backhauled small cells, where multiple FD capable small cell base stations (SBS) are wirelessly backhauled by a FD capable macro-cell BS (MBS). To increase the capacity of the backhaul link, the MBS is equipped with multiple antennas to enable space division multiple access (SDMA). A scheduling method using back-pressure algorithm and geometric programming is proposed for link selection and interference mitigation. Simulation results show that with FD SDMA backhaul links, the proposed scheduler almost doubles throughput under asymmetric traffic demand and various network conditions.

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arXiv2017

Restless Video Bandits: Optimal SVC Streaming in a Multi-user Wireless Network

In this paper, we consider the problem of optimal scalable video delivery to mobile users in wireless networks given arbitrary Quality Adaptation (QA) mechanisms. In current practical systems, QA and scheduling are performed independently by the content provider and network operator, respectively. While most research has been focused on jointly optimizing these two tasks, the high complexity that comes with a joint approach makes the implementation impractical. Therefore, we present a scheduling mechanism that takes the QA logic of each user as input and optimizes the scheduling accordingly. Hence, there is no need for centralized QA and cross-layer interactions are minimized. We model the QA-adaptive scheduling and the jointly optimal problem as a Restless Bandit and a Multi-user Semi Markov Decision Process, respectively in order to compare the loss incurred by not employing a jointly optimal scheme. We then present heuristic algorithms in order to achieve the optimal outcome of the Restless Bandit solution assuming the base station has knowledge of the underlying quality adaptation of each user (QA-Aware). We also present a simplified heuristic without the need for any higher layer knowledge at the base station (QA-Blind). We show that our QA-Aware strategy can achieve up to two times improvement in user network utilization compared to popular baseline algorithms such as Proportional Fairness. We also provide a testbed implementation of the QA-Blind scheme in order to compare it with baseline algorithms in a real network setting.

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arXiv2017

Resource Sharing Among mmWave Cellular Service Providers in a Vertically Differentiated Duopoly

With the increasing interest in the use of millimeter wave bands for 5G cellular systems comes renewed interest in resource sharing. Properties of millimeter wave bands such as massive bandwidth, highly directional antennas, high penetration loss, and susceptibility to shadowing, suggest technical advantages to spectrum and infrastructure sharing in millimeter wave cellular networks. However, technical advantages do not necessarily translate to increased profit for service providers, or increased consumer surplus. In this paper, detailed network simulations are used to better understand the economic implications of resource sharing in a vertically differentiated duopoly market for cellular service. The results suggest that resource sharing is less often profitable for millimeter wave service providers compared to microwave cellular service providers, and does not necessarily increase consumer surplus.

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arXiv2016

Directional Initial Access for Millimeter Wave Cellular Systems

The millimeter wave (mmWave) bands have recently attracted considerable interest for next-generation cellular systems due to the massive available bandwidths at these frequencies. However, a key challenge in designing mmWave cellular systems is initial access -- the procedure by which a mobile establishes an initial link-layer connection to a base station cell. MmWave communication relies on highly directional transmissions and the initial access procedure must thus provide a mechanism by which initial transmission directions can be searched in a potentially large angular space. Design options are compared considering different scanning and signaling procedures to evaluate access delay and system overhead. The channel structure and multiple access issues are also considered. The analysis demonstrates significant benefits of low-resolution fully digital architectures in comparison to single stream analog beamforming.

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arXiv2016

Spectrum and Infrastructure Sharing in Millimeter Wave Cellular Networks: An Economic Perspective

The licensing model for millimeter wave bands has been the subject of considerable debate, with some industry players advocating for unlicensed use and others for traditional geographic area exclusive use licenses. Meanwhile, the massive bandwidth, highly directional antennas, high penetration loss and susceptibility to shadowing in these bands suggest certain advantages to spectrum and infrastructure sharing. However, even when sharing is technically beneficial (as recent research in this area suggests that it is), it may not be profitable. In this paper, both the technical and economic implications of resource sharing in millimeter wave networks are studied. Millimeter wave service is considered in the economic framework of a network good, where consumers' utility depends on the size of the network, and the strategic decisions of consumers and service providers are connected to detailed network simulations. The results suggest that "open" deployments of neutral small cells that serve subscribers of any service provider encourage market entry by making it easier for networks to reach critical mass, more than "open" (unlicensed) spectrum would. The conditions under which competitive service providers would prefer to share resources or not are also described.

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arXiv2016

Under a cloud of uncertainty: Legal questions affecting Internet storage and transmission of copyright-protected video content

The rapid growth of multimedia consumption has triggered technical, economic, and business innovations that improve the quality and accessibility of content. It has also opened new markets, promising large revenues for industry players. However, new technologies also pose new questions regarding the legal aspects of content delivery, which are often resolved through litigation between copyright owners and content distributors. The precedents set by these cases will act as a game changer in the content delivery industry and will shape the existing offerings in the market in terms of how new technologies can be deployed and what kind of pricing strategies can be associated with them. In this paper, we offer a tutorial on key copyright and communications laws and decisions related to storage and transmission of video content over the Internet. We summarize legal limitations on the deployment of new technologies and pricing mechanisms, and explain the implications of recent lawsuits. Understanding these concerns is essential for engineers engaged in designing the technical and economic aspects of video delivery systems.

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arXiv2015

SVC-based Multi-user Streamloading for Wireless Networks

In this paper, we present an approach for joint rate allocation and quality selection for a novel video streaming scheme called streamloading. Streamloading is a recently developed method for delivering high quality video without violating copyright enforced restrictions on content access for video streaming. In regular streaming services, content providers restrict the amount of viewable video that users can download prior to playback. This approach can cause inferior user experience due to bandwidth variations, especially in mobile networks with varying capacity. In streamloading, the video is encoded using Scalable Video Coding, and users are allowed to pre-fetch enhancement layers and store them on the device, while base layers are streamed in a near real-time fashion ensuring that buffering constraints on viewable content are met. We begin by formulating the offline problem of jointly optimizing rate allocation and quality selection for streamloading in a wireless network. This motivates our proposed online algorithms for joint scheduling at the base station and segment quality selection at receivers. The results indicate that streamloading outperforms state-of-the-art streaming schemes in terms of the number of additional streams we can admit for a given video quality. Furthermore, the quality adaptation mechanism of our proposed algorithm achieves a higher performance than baseline algorithms with no (or limited) video-centric optimization of the base station's allocation of resources, e.g., proportional fairness.

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arXiv2015

Directional Cell Discovery in Millimeter Wave Cellular Networks

The acute disparity between increasing bandwidth demand and available spectrum, has brought millimeter wave (mmW) bands to the forefront of candidate solutions for the next-generation cellular networks. Highly directional transmissions are essential for cellular communication in these frequencies to compensate for high isotropic path loss. This reliance on directional beamforming, however, complicates initial cell search since the mobile and base station must jointly search over a potentially large angular directional space to locate a suitable path to initiate communication. To address this problem, this paper proposes a directional cell discovery procedure where base stations periodically transmit synchronization signals, potentially in time-varying random directions, to scan the angular space. Detectors for these signals are derived based on a Generalized Likelihood Ratio Test (GLRT) under various signal and receiver assumptions. The detectors are then simulated under realistic design parameters and channels based on actual experimental measurements at 28~GHz in New York City. The study reveals two key findings: (i) digital beamforming can significantly outperform analog beamforming even when the digital beamforming uses very low quantization to compensate for the additional power requirements; and (ii) omni-directional transmissions of the synchronization signals from the base station generally outperforms random directional scanning.

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arXiv2014

Distributed Scheduling Algorithms for Crosspoint-Buffered Switches

Given the rapid increase in traffic, greater demands have been put on high-speed switching systems. Such systems have to simultaneously meet several constraints, e.g., high throughput, low delay and low complexity. This makes it challenging to design an efficient scheduling algorithm, and has consequently drawn considerable research interest. However, previous results either cannot provide a $100\%$ throughput guarantee without a speedup, or require a complex centralized scheduler. In this paper, we design a {\it distributed} $100 \%$ throughput algorithm for crosspoint buffered switches, called DISQUO, with very limited message passing. We prove that DISQUO can achieve $100\%$ throughput for any admissible Bernoulli traffic, with a low time complexity of $O(1)$ per port. To the best of our knowledge, it is the first distributed algorithm that can provide a $100\%$ throughput for a crosspoint buffered switch.

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arXiv2014

Technical Report: Efficient Buffering and Scheduling for a Single-Chip Crosspoint-Queued Switch

The single-chip crosspoint-queued (CQ) switch is a compact switching architecture that has all its buffers placed at the crosspoints of input and output lines. Scheduling is also performed inside the switching core, and does not rely on latency-limited communications with input or output line-cards. Compared with other legacy switching architectures, the CQ switch has the advantages of high throughput, minimal delay, low scheduling complexity, and no speedup requirement. However, the crosspoint buffers are small and segregated, thus how to efficiently use the buffers and avoid packet drops remains a major problem that needs to be addressed. In this paper, we consider load balancing, deflection routing, and buffer pooling for efficient buffer sharing in the CQ switch. We also design scheduling algorithms to maintain the correct packet order even while employing multi-path switching and resolve contentions caused by multiplexing. All these techniques require modest hardware modifications and memory speedup in the switching core, but can greatly boost the buffer utilizations by up to 10 times and reduce the packet drop rates by one to three orders of magnitude. Extensive simulations and analyses have been done to demonstrate the advantages of the proposed buffering and scheduling techniques in various aspects. By pushing the on-chip memory to the limit of current ASIC technology, we show that a cell drop rate of 10e-8, which is low enough for practical uses, can be achieved under real Internet traffic traces corresponding to a load of 0.9.

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arXiv2013

A Truthful Auction based Incentive Framework for Femtocell Access

As cellular operators are suffering from a data explosion problem, and users are consequently experiencing poor data services, the introduction of femtocells offers a cost-effective way to mitigate this problem. Femtocells enable larger network capacity by increasing spatial reuse of the spectrum and shortening the distance to the users. Existing work has shown that open access femtocells, which allow unregistered macro users to connect, are efficient in reducing inter-cell interference and offloading traffic. However, a major obstacle constraining the potential capability of femtocells and open access is the lack of incentives for privately-owned femtocells to serve unregistered users. Hence in this paper, we propose a Vickrey-Clarke-Groves (VCG) auction based incentive framework for accessing such selfish femtocells. We consider two scenarios: One scenario involves a single macro user and another scenario has multiple macro users. We design auction schemes for both scenarios and show analytically that our schemes are truthful and have low computational complexity. Extensive simulations validate these properties and show huge performance improvement to the macro users.

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