arXiv subjects

Monisha Ghosh

Publications and source records attributed to Monisha Ghosh.

30 records · Page 2Linked to original sources

arXiv2022

Impact of Device Thermal Performance on 5G mmWave Communication Systems

5G millimeter wave (mmWave) cellular networks have been reported to deliver 1-2 Gbps downlink throughput, via speed-tests. However, these speed-tests capture only a few seconds of throughput and are not representative of sustained throughput over several minutes. We report the first measurements of sustained throughput in three cities, Miami, Chicago, and San Francisco, where we observe throughput throttling due to rising skin temperature of the phone when it is connected to a deployed 5G mmWave base-station (BS). Radio Resource Control (RRC) messaging between the phone and the BS indicates the reduction in the number of aggregated mmWave channels from 4 to 1 followed by a switch to 4G. We corroborate these measurements with infra-red images as the phone heats up. Thus, mmWave throughput will be limited not by network characteristics but by device thermal management.

cs.NI↗

arXiv2021

A Comparison Study of Cellular Deployments in Chicago and Miami Using Apps on Smartphones

Cellular operators have begun deploying 5G New Radio (NR) in all available bands: low (< 1 GHz), mid (1 - 6 GHz), and high (> 24 GHz) to exploit the different capabilities of each. At the same time, traditional 4G Long Term Evolution (LTE) deployments are being enhanced with the addition of bands in the unlicensed 5 GHz (using License Assisted Access, or LAA) and the 3.5 GHz Citizens Broadband Radio Service (CBRS) resulting in throughput performance comparable to 5G in mid-band. We present a detailed study comparing 4G and 5G deployments, in all bands in Chicago, and focused mmWave measurements and analysis in Miami. Our methodology, based on commercial and custom apps, is scalable for crowdsourcing measurements on a large scale and provides detailed data (throughput, latency, signal strength, etc.) on actual deployments. Our main conclusions based on the measurements are (i) optimized 4G networks in mid-band are comparable in both throughput and latency to current deployments of 5G (both standalone (SA) and non-standalone (NSA)) and (ii) mmWave 5G, even in NSA mode, can deliver multi-Gbps throughput reliably if the installation is dense enough, but performance is still brittle due to the propagation limitations imposed by distance and body loss. Thus, while 5G demonstrates significant early promise, further work needs to be done to ensure that the stated goals of 5G are met.

cs.NI↗

arXiv2021

Hidden-nodes in coexisting LAA & Wi-Fi: a measurement study of real deployments

LTE-Licensed Assisted Access (LAA) networks are beginning to be deployed widely in major metropolitan areas in the US in the unlicensed 5 GHz bands, which have existing dense deployments of Wi-Fi. This provides a real-world opportunity to study the problems due to hidden-node scenarios between LAA and Wi-Fi. The hidden node problem has been well studied in the context of overlapping Wi-Fi APs. However, when Wi-Fi coexists with LAA, the hidden node problem is exacerbated since LAA cannot use the well-known Request-to-Send (RTS)/Clear to-Send (CTS) mechanism to resolve contentions, resulting in throughput degradation for Wi-Fi. In this paper, we describe detailed measurements and conclusions from experiments on the campus of the University of Chicago which presents a perfect hidden node scenario where Wi-Fi access points (APs) controlled by us and an LAA base-station (BS) deployed by AT&T are hidden from each other, but the clients are not. We performed careful experiments in three different regions of the coexistence area: (i) clients midway between LAA & Wi-Fi; (ii) clients close to the Wi-Fi AP; and (iii) clients close to the LAA BS. Our results show that in a situation where LAA uses an aggregate of three unlicensed channels (60 MHz bandwidth) which overlap with an 80 MHz Wi-Fi transmission, the Wi-Fi throughput at client devices suffers considerably. Overall, Wi-Fi performance is impacted by the hidden node problem more severely than LAA. In the best outdoor conditions, the throughput of LAA and Wi-Fi is reduced by 35% and 97% respectively when coexisting with each other as compared when the other system is not present. Furthermore, we conclude that when both LAA and Wi-Fi use multiple 20 MHz channels and there are multiple Wi-Fi APs coexisting with LAA on the same set of channels, the choice of Wi-Fi primary channels can have a significant impact on LAA throughput.

cs.NI↗

arXiv2020

Measurement-based coexistence studies of LAA & Wi-Fi deployments in Chicago

LTE-Licensed Assisted Access (LAA) networks are beginning to be deployed widely in major metropolitan areas in the US in the unlicensed 5 GHz bands, which have existing dense deployments of Wi-Fi as well. Various aspects of the coexistence scenarios such deployments give rise to have been considered ina vast body of academic and industry research. However, there is very little data and research on how these coexisting networks will behave in practice. The question of fair coexistence between Wi-Fi and LAA has moved from a theoretical question to reality. The recent roll-out of LAA deployments provides an opportunity to collect data on the operation of these networks as well as studying coexistence issues on the ground. In this paper we describe the first results of a measurement campaign conducted over many months, using custom apps as well as off-the-shelf tools, in several areas of Chicago where the major carriers have been expanding LAA deployments. The measurements reveal that coexistence between LAA and Wi-Fi in dense, urban environments where both systems aggregate multiple channels, continues to be a challenging problem that requires further research.

cs.NI↗

arXiv2020

Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios

The application of Machine Learning (ML) techniques to complex engineering problems has proved to be an attractive and efficient solution. ML has been successfully applied to several practical tasks like image recognition, automating industrial operations, etc. The promise of ML techniques in solving non-linear problems influenced this work which aims to apply known ML techniques and develop new ones for wireless spectrum sharing between Wi-Fi and LTE in the unlicensed spectrum. In this work, we focus on the LTE-Unlicensed (LTE-U) specification developed by the LTE-U Forum, which uses the duty-cycle approach for fair coexistence. The specification suggests reducing the duty cycle at the LTE-U base-station (BS) when the number of co-channel Wi-Fi basic service sets (BSSs) increases from one to two or more. However, without decoding the Wi-Fi packets, detecting the number of Wi-Fi BSSs operating on the channel in real-time is a challenging problem. In this work, we demonstrate a novel ML-based approach which solves this problem by using energy values observed during the LTE-U OFF duration. It is relatively straightforward to observe only the energy values during the LTE-U BS OFF time compared to decoding the entire Wi-Fi packet, which would require a full Wi-Fi receiver at the LTE-U base-station. We implement and validate the proposed ML-based approach by real-time experiments and demonstrate that there exist distinct patterns between the energy distributions between one and many Wi-Fi AP transmissions. The proposed ML-based approach results in a higher accuracy (close to 99\% in all cases) as compared to the existing auto-correlation (AC) and energy detection (ED) approaches.

cs.NI↗

arXiv2019

Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT

According to the LTE-U Forum specification, a LTE-U base-station (BS) reduces its duty cycle from 50% to 33% when it senses an increase in the number of co-channel Wi-Fi basic service sets (BSSs) from one to two. The detection of the number of Wi-Fi BSSs that are operating on the channel in real-time, without decoding the Wi-Fi packets, still remains a challenge. In this paper, we present a novel machine learning (ML) approach that solves the problem by using energy values observed during LTE-U OFF duration. Observing the energy values (at LTE-U BS OFF time) is a much simpler operation than decoding the entire Wi-Fi packets. In this work, we implement and validate the proposed ML based approach in real-time experiments, and demonstrate that there are two distinct patterns between one and two Wi-Fi APs. This approach delivers an accuracy close to 100% compared to auto-correlation (AC) and energy detection (ED) approaches.

cs.NI↗

arXiv2019

Interference Management in UAV-assisted Integrated Access and Backhaul Cellular Networks

An integrated access and backhaul (IAB) network architecture can enable flexible and fast deployment of next-generation cellular networks. However, mutual interference between access and backhaul links, small inter-site distance and spatial dynamics of user distribution pose major challenges in the practical deployment of IAB networks. To tackle these problems, we leverage the flying capabilities of unmanned aerial vehicles (UAVs) as hovering IAB-nodes and propose an interference management algorithm to maximize the overall sum rate of the IAB network. In particular, we jointly optimize the user and base station associations, the downlink power allocations for access and backhaul transmissions, and the spatial configurations of UAVs. We consider two spatial configuration modes of UAVs: distributed UAVs and drone antenna array (DAA), and show how they are intertwined with the spatial distribution of ground users. Our numerical results show that the proposed algorithm achieves an average of $2.9\times$ and $6.7\times$ gains in the received downlink signal-to-interference-plus-noise ratio (SINR) and overall network sum rate, respectively. Finally, the numerical results reveal that UAVs cannot only be used for coverage improvement but also for capacity boosting in IAB cellular networks.

eess.SP↗

arXiv2019

Angle Feedback for NOMA Transmission in mmWave Drone Networks

In this paper, we consider an unmanned aerial vehicle (UAV) based wireless network using non-orthogonal multiple access (NOMA) transmission in millimeter-wave frequencies to deliver broadband data in a spectrally efficient fashion at hotspot scenarios. The necessity for the NOMA transmitter to gather information on user channel quality becomes a major drawback in practical deployments. We therefore consider various limited feedback schemes for NOMA transmission, to relieve the complexity of tracking and feeding back the full channel state information (CSI) of the users. In particular, through beamforming we allow NOMA to exploit the space domain, and hence the user angle emerges as a promising (yet novel) limited feedback scheme. We show that as the user region for NOMA transmission gets wider, the users become more distinctive at the transmitter side with respect to their angles, making user angle feedback a better alternative than distance feedback in such scenarios. We rigorously derive and analyze the outage sum rate performance for NOMA transmission considering various user ordering strategies involving full CSI, angle, and distance feedback schemes. Our analytical results for NOMA outage sum rates using those feedback schemes match closely with simulations, and provide useful insights on properly choosing a limited feedback scheme for different deployment geometries and operating configurations.

cs.IT↗

arXiv2018

UAV-Based in-band Integrated Access and Backhaul for 5G Communications

We introduce the concept of using unmanned aerial vehicles (UAVs) as drone base stations for in-band Integrated Access and Backhaul (IB-IAB) scenarios for 5G networks. We first present a system model for forward link transmissions in an IB-IAB multi-tier drone cellular network. We then investigate the key challenges of this scenario and propose a framework that utilizes the flying capabilities of the UAVs as the main degree of freedom to find the optimal precoder design for the backhaul links, user-base station association, UAV 3D hovering locations, and power allocations. We discuss how the proposed algorithm can be utilized to optimize the network performance in both large and small scales. Finally, we use an exhaustive search-based solution to demonstrate the performance gains that can be achieved from the presented algorithm in terms of the received signal to interference plus noise ratio (SINR) and overall network sum-rate.

eess.SP↗

arXiv2018

Analysis of CSAT performance in Wi-Fi and LTE-U Coexistence

In this paper, we study energy-based Carrier Sense Adaptive Transmission (CSAT) for use with LTE-U and investigate the performance in Wi-Fi/LTE-U coexistence using theoretical analysis and experimental verification using NI USRPs. According to the LTE-U forum specification, if an LTE-U base station (BS) finds a vacant channel, it can transmit for up to 20 ms and turn OFF its transmission for only 1 ms, resulting in a maximum duty cycle of 95%. In a dense deployment of LTE-U and Wi-Fi, it is very likely that a Wi-Fi access point (AP) will wish to use the same channel. It will start transmission by trying to transmit association packets (using carrier sense multiple access with collision avoidance (CSMA/CA)) through the 1 ms LTE-U OFF duration. Since this duration is very small, it leads to increased association packet drops and thus delays the Wi-Fi association process. Once LTE-U, using CSAT, detects Wi-Fi, it should scale back the duty cycle to 50%. We demonstrate in this paper, using an experimental platform as well as theoretical analysis, that if LTE-U is using a 95% duty cycle, energy based CSAT will take a much longer time to scale back the duty cycle due to the beacon drops and delays in the reception. Hence, in order to maintain association fairness with Wi-Fi, we propose that a LTE-U BS should not transmit at maximum duty cycles (95%), even if the channel is sensed to be vacant.

cs.NI↗

arXiv2018

Analytical Modeling of Wi-Fi and LTE-LAA Coexistence: Throughput and Impact of Energy Detection Threshold

With both small-cell LTE and Wi-Fi networks available as alternatives for deployment in unlicensed bands (notably 5 GHz), the investigation into their coexistence is a topic of active interest, primarily driven by industry groups. 3GPP has recently standardized LTE Licensed Assisted Access (LTE-LAA) that seeks to make LTE more co-existence friendly with Wi-Fi by incorporating similar sensing and back-off features. Nonetheless, the results presented by industry groups offer little consensus on important issues like respective network parameter settings that promote "fair access" as required by 3GPP. Answers to such key system deployment aspects, in turn, require credible analytical models, on which there has been little progress to date. Accordingly, in one of the first work of its kind, we develop a new framework for estimating the throughput of Wi-Fi and LTE-LAA in coexistence scenarios via suitable modifications to the celebrated Bianchi \cite{Bianchi} model. The impact of various network parameters such as energy detection (ED) threshold on Wi-Fi and LTE-LAA coexistence is explored as a byproduct and corroborated via a National Instrument (NI) experimental testbed that validates the results for LTE-LAA access priority class 1 and 3.

cs.NI↗

arXiv2018

Association fairness in Wi-Fi and LTE-U coexistence

In this paper we address the issue of association fairness when Wi-Fi and LTE unlicensed (LTE-U) coexist on the same channel in the unlicensed 5 GHz band. Since beacon transmission is the first step in starting the association process in Wi-Fi, we define association fairness as how fair LTE-U is in allowing Wi-Fi to start transmitting beacons on a channel that it occupies with a very large duty cycle. According to the LTE-U specification, if a LTE-U base station determines that a channel is vacant, it can transmit for up to 20 ms and turn OFF for only 1 ms, resulting in a duty cycle of 95%. In an area with heavy spectrum usage, there will be cases when a Wi-Fi access point wishes to share the same channel, as it does today with Wi-Fi. We study, both theoretically and experimentally, the effect that such a large LTE-U duty cycle can have on the association process, specifically Wi-Fi beacon transmission and reception. We demonstrate via an experimental set-up using National Instrument (NI) USRPs that a significant percentage of Wi-Fi beacons will either not be transmitted in a timely fashion or will not be received at the LTE-U BS thus making it difficult for the LTE-U BS to adapt its duty cycle in response to the Wi-Fi usage. Our experimental results corroborate our theoretical analysis. We compare the results with Wi-Fi/Wi-Fi coexistence and demonstrate that LTE-U/Wi-Fi coexistence is not fair when it comes to initial association since there is a much larger percentage of beacon errors in the latter case. Hence, the results in the paper indicate that in order to maintain association fairness, a LTE-U BS should not transmit at such high duty cycles, even if it deems the channel to be vacant.

eess.SP↗