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A bipartite experiment consists of one set of units being assigned treatments and another set of units for which we measure outcomes. The two sets of units are connected by a bipartite graph, governing how the treated units can affect the outcome units. The bipartite framework naturally arises in marketplace experiments where, for example, experimenters may seek to investigate the effect of discounting goods on buyer behavior. In this paper, we consider estimation of the average total treatment effect in the bipartite experimental framework under a linear exposure-response model. We introduce the Exposure Reweighted Linear (ERL) estimator, and show that the estimator is unbiased, consistent and asymptotically normal, provided that the bipartite graph is sufficiently sparse. To facilitate inference, we introduce an unbiased and consistent estimator of the variance of the ERL point estimator. In addition, we introduce a cluster-based design, Exposure-Design, that uses heuristics to increase the precision of the ERL estimator by realizing a desirable exposure distribution. Finally, we demonstrate the application of the described methodology to marketplace experiments using a publicly available Amazon user-item review dataset. The full version of the paper is available at: https://arxiv.org/abs/2103.06392. [ABSTRACT FROM AUTHOR]

This paper answers a simple but important question in VANET research: what is the optimal data rate to be used in DSRC-based vehicle safety communications? While it is generally accepted that the default choice is 6 Mbps, this assumption is not rooted in strong technical considerations. This paper provides a systematic evaluation of optimized data rates choices in a variety of scenarios. The answer found enables researchers to generally eliminate one dimension of complexity in relevant VANET studies. Additionally, the methodology used in this paper is possibly as interesting as the conclusion. [ABSTRACT FROM AUTHOR]

In 802.11 managed wireless networks, the manager can address under-served links by rate-limiting the conflicting nodes. In order to determine to what extent each conflicting node is responsible for the poor performance, the manager needs to understand the coordination among conflicting nodes' transmissions. In this paper, we present a management framework called MIDAS (Management, Inference, and Diagnostics using Activity Share). We introduce the concept of Activity Share which characterizes the coordination among any set of network nodes in terms of the time they spend transmitting simultaneously. Unfortunately, the Activity Share cannot be locally measured by the nodes. Thus, MIDAS comprises an inference tool which, based on a combined physical, protocol, and statistical approach, infers the Activity Share by using a small set of passively collected, time-aggregate local channel measurements reported by the nodes. MIDAS uses the estimated Activity Share as the input of a simple model that predicts how limiting the transmission rate of any conflicting node would benefit the throughput of the under-served link. The model is based on the current network conditions, thus representing the first throughput model using online measurements. We implemented our tool on real hardware and deployed it on an indoor testbed. Our extensive validation combines testbed experiments and simulations. The results show that MIDAS infers the Activity Share with an average normalized relative error below 12% in all testbed experiments. [ABSTRACT FROM AUTHOR]

Interference is a critical issue in wireless communications. In a typical multiple-user environment, different users may severely interfere with each other. Coordination among users therefore is an indispensable part for interference management in wireless networks. It is known that, coordination among multiple nodes is a costly operation taking a significant amount of valuable communication resource. In this paper, we have an interesting observation that by generating intended patterns, some simultaneous transmissions, i.e., "interference", can be successfully decoded without degrading the effective throughput in original transmission. As such, an extra and "free" coordination channel can be built. Based on this idea we propose a DC-MAC to leverage this "free" channel for efficient medium access in a multiple-user wireless network. We theoretically analyze the capacity of this channel under different environments with various modulation schemes. USRP2-based implementation experiments show that compared with the widely adopted CSMA, DC-MAC can improve the channel utilization efficiency by up to 250%. [ABSTRACT FROM AUTHOR]

Interference is a critical issue in wireless communications. In a typical multiple-user environment, different users may severely interfere with each other. Coordination among users therefore is an indispensable part for interference management in wireless networks. It is known that, coordination among multiple nodes is a costly operation taking a significant amount of valuable communication resource. In this paper, we have an interesting observation that by generating intended patterns, some simultaneous transmissions, i.e., "interference", can be successfully decoded without degrading the effective throughput in original transmission. As such, an extra and "free" coordination channel can be built. Based on this idea we propose a DC-MAC to leverage this "free" channel for efficient medium access in a multiple-user wireless network. We theoretically analyze the capacity of this channel under different environments with various modulation schemes. USRP2-based implementation experiments show that compared with the widely adopted CSMA, DCMAC can improve the channel utilization efficiency by up to 250%. [ABSTRACT FROM AUTHOR]

A multihop underwater acoustic network, which consists of a series of equal-distance hops connected by relay transceivers in a tandem, is considered. Messages are originated as coded packets from a source node at one end, relayed (decoded and re-encoded) sequentially hop by hop, and finally received by a destination node at the other end of the network. Several key characteristics of underwater acoustic channels, namely, frequency-dependent signal attenuation and noise, inter-hop interference, half-duplex constraint, and large propagation delay, are taken into account in the analysis. A simple transmission protocol with spatial reuse is considered, and the transmission schedule is designed to satisfy the half-duplex constraint on relay transceivers in the presence of large propagation delay. To efficiently cope with frequency-dependent channel characteristic and inter-hop interference, the power spectral density function of signaling is analytically optimized in a way analogous to water-filling. Furthermore, the problem of determining the minimum number of hops to support a pre-specified rate and reliability with and without a maximum coded packet length constraint is examined. Finally, numerical results are presented to illustrate the analysis. [ABSTRACT FROM AUTHOR]

Experimentation is the foundation of scientific decision-making on online marketplaces and social networks. However, experiments often suffer from interference where intervening on a participant impacts the outcome of other participants. Under general interference, the causal effect cannot be identified even in a randomized experiment. Interference is especially problematic in marketplaces, where strategic agents compete for scarce resources. For example, consider an experiment comparing two different policies for selecting the reserve price in a second-price advertising auction. Changes in the reserve price ("treatment / intervention") for some advertisers (bidders) can affect other advertisers through market competition, impacting the outcomes of even untreated advertisers. [ABSTRACT FROM AUTHOR]

We present a measurement study of wireless experience in a diverse set of home environments by deploying an infrastructure, we call WiSe. Our infrastructure consists of OpenWrt-based Access Points (APs) that have been given away to residents for free to be installed as their primary wireless access mechanism. These APs are configured with our specialized measurement and monitoring software that communicates with our measurement controller through an open API. We have collected wireless performance traces from 30 homes for a period in excess of 6 months. To analyze the characteristics of these home wireless environments, we have also developed a simple metric that estimates the likely TCP throughput different clients can expect based on current channel and environmental conditions. With this infrastructure, we provide multiple quantitative observations, some of which are anecdotally understood in our community. For example, while a majority of links performed well most of the time, we observed cases of poor client experience about 2.1% of the total time. [ABSTRACT FROM AUTHOR]

WiFi networks have enjoyed an unprecedent penetration rate in recent years. However, due to the limited coverage, existing WiFi infrastructure only provides intermittent connectivity for mobile users. Once leaving the current network coverage, WiFi clients must actively discover new WiFi access points (APs), which wastes the precious energy of mobile devices. Although several solutions have been proposed to address this issue, they either require significant modifications to existing network infrastructures or rely on context information that is not available in unknown environments. In this work, we develop a system called ZiFi that utilizes ZigBee radios to identify the existence of WiFi networks through unique interference signatures generated by WiFi beacons. We develop a new digital signal processing algorithm called Common Multiple Folding (CMF) that accurately amplifies periodic beacons in WiFi interference signals. ZiFi also adopts a constant false alarm rate (CFAR) detector that can minimize the false negative (FN) rate of WiFi beacon detection while satisfying the user-specified upper bound on false positive (FP) rate. We have implemented ZiFi on two platforms, a Linux netbook integrating a TelosB mote through the USB interface, and a Nokia N73 smartphone integrating a ZigBee card through the miniSD interface. Our experiments show that, under typical settings, ZiFi can detect WiFi APs with high accuracy (<5% total FP and FN rate), short delay (~780 ms), and little computation overhead [ABSTRACT FROM AUTHOR]

WiFi networks have enjoyed an unprecedent penetration rate in recent years. However, due to the limited coverage, existing WiFi infrastructure only provides intermittent connectivity for mobile users. Once leaving the current network coverage, WiFi clients must actively discover new WiFi access points (APs), which wastes the precious energy of mobile devices. Although several solutions have been proposed to address this issue, they either require significant modifications to existing network infrastructures or rely on context information that is not available in unknown environments. In this work, we develop a system called ZiFi that utilizes ZigBee radios to identify the existence of WiFi networks through unique interference signatures generated by WiFi beacons. We develop a new digital signal processing algorithm called Common Multiple Folding (CMF) that accurately amplifies periodic beacons in WiFi interference signals. ZiFi also adopts a constant false alarm rate (CFAR) detector that can minimize the false negative (FN) rate of WiFi beacon detection while satisfying the user-specified upper bound on false positive (FP) rate. We have implemented ZiFi on two platforms, a Linux netbook integrating a TelosB mote through the USB interface, and a Nokia N73 smartphone integrating a ZigBee card through the miniSD interface. Our experiments show that, under typical settings, ZiFi can detect WiFi APs with high accuracy (< 5% total FP and FN rate), short delay (~ 780 ms), and little computation overhead. [ABSTRACT FROM AUTHOR]

We consider the problem of cross-band interference when devices from the same or different networks share radio spectrum. Cross-band interference occurs when unsynchronized transmissions create harmful interference among each other although they use non-overlapping frequency bands. We perform an in-depth study to analytically quantify the degree of interference and its impact on OFDMA-based packet transmissions. The analysis also takes into account practical artifacts including temporal sampling mismatch, frequency offset and power heterogeneity. Using insights from the analysis, we build and compare three methods that apply temporal and frequency redundancy to reduce the interference and add robustness against it. Experimental and analytical results show that adding frequency guardband is the most efficient solution to tackle cross-band interference. [ABSTRACT FROM AUTHOR]

We consider the problem of cross-band interference when devices from the same or different networks share radio spectrum. Cross-band interference occurs when unsynchronized transmissions create harmful interference among each other although they use non-overlapping frequency bands. We perform an in-depth study to analytically quantify the degree of interference and its impact on OFDMA-based packet transmissions. The analysis also takes into account practical artifacts including temporal sampling mismatch, frequency offset and power heterogeneity. Using insights from the analysis, we build and compare three methods that apply temporal and frequency redundancy to reduce the interference and add robustness against it. Experimental and analytical results show that adding frequency guardband is the most efficient solution to tackle cross-band interference. [ABSTRACT FROM AUTHOR]

In a wireless network it is important to understand the nature of the joint interference generated at a receiver by multiple concurrent transmitters. This understanding helps developing packet scheduling algorithms. Prior experimental work using older generation mote-class radios (CC1000) have showed systematic deviations between estimation and direct measurement of the joint interference power, thus questioning whether the standard assumption that received signal powers are additive is applicable in practice. We, however, show via extensive experimentation that on newer generation radios (CC2420), the additive assumption is valid, particularly at the low power end. [ABSTRACT FROM AUTHOR]

We develop an analytical framework to study experimental design in two-sided platforms. In the settings we consider, customers rent listings; rented listings are occupied for some amount of time, then become available. Platforms typically use two common designs to study interventions in such settings: customer-side randomization (CR), and listing-side randomization (LR), along with associated estimators. We develop a stochastic model and associated mean field limit to capture dynamics in such systems, and use our model to investigate how the performance of these estimators is affected by interference effects between listings and between customers. Good experimental design depends on market balance: we show that in highly demand-constrained markets, CR is unbiased, while LR is biased; conversely, in highly supply-constrained markets, LR is unbiased, while CR is biased. We also study a design based on two-sided randomization (TSR) where both customers and listings are randomized to treatment and control, and show that appropriate choices of such designs can be unbiased in both extremes of market balance, and also yield low bias in intermediate regimes of market balance. [ABSTRACT FROM AUTHOR]