The growing commercial interest in indoor location-based services (ILBS) has spurred recent development of many indoor positioning techniques. Due to the absence of global positioning system (GPS) signal, many other signals have been proposed for indoor usage. Among them, Wi-Fi (802.11) emerges as a promising one due to the pervasive deployment of wireless LANs (WLANs). In particular, Wi-Fi fingerprinting has been attracting much attention recently because it does not require line-of-sight measurement of access points (APs) and achieves high applicability in complex indoor environment. This survey overviews recent advances on two major areas of Wi-Fi fingerprint localization: advanced localization techniques and efficient system deployment. Regarding advanced techniques to localize users, we present how to make use of temporal or spatial signal patterns, user collaboration, and motion sensors. Regarding efficient system deployment, we discuss recent advances on reducing offline labor-intensive survey, adapting to fingerprint changes, calibrating heterogeneous devices for signal collection, and achieving energy efficiency for smartphones. We study and compare the approaches through our deployment experiences, and discuss some future directions.

/pdf/wi-fi-fingerprint-based-indoor-positioning-recent-advances-1sxd8ckwi0.pdf

Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons

Visible Light Positioning (VLP) provides a promising means to achieve indoor localization with sub-meter accuracy. We observe that the Visible Light Communication (VLC) methods in existing VLP systems rely on intensity-based modulation, and thus they require a high pulse rate to prevent flickering. However, the high pulse rate adds an unnecessary and heavy burden to receiving devices. To eliminate this burden, we propose the polarization-based modulation, which is flicker-free, to enable a low pulse rate VLC. In this way, we make VLP light-weight enough even for resourceconstrained wearable devices, e.g. smart glasses. Moreover, the polarization-based VLC can be applied to any illuminating light sources, thereby eliminating the dependency on LED. This paper presents the VLP system PIXEL, which realizes our idea. In PIXEL, we develop three techniques, each of which addresses a design challenge: 1) a novel color-based modulation scheme to handle users’ mobility, 2) an adaptive downsampling algorithm to tackle the uneven sampling problem of wearables’ low-cost camera and 3) a computational optimization method for the positioning algorithm to enable real-time processing. We implement PIXEL’s hardware using commodity components and develop a software program for both smartphone and Google glass. Our experiments based on the prototype show that PIXEL can provide accurate realtime VLP for wearables and smartphones with camera resolution as coarse as 60 pixel 80 pixel and CPU frequency as low as 300MHz.

/pdf/wearables-can-afford-light-weight-indoor-positioning-with-54z10zkb1f.pdf

Wearables Can Afford: Light-weight Indoor Positioning with Visible Light (Best Paper Candidate, Best Video Presentation Award)

Visible Light Positioning (VLP) provides a promising means to achieve indoor localization with sub-meter accuracy. We observe that the Visible Light Communication (VLC) methods in existing VLP systems rely on intensity-based modulation, and thus they require a high pulse rate to prevent flickering. However, the high pulse rate adds an unnecessary and heavy burden to receiving devices. To eliminate this burden, we propose the polarization-based modulation, which is flicker-free, to enable a low pulse rate VLC. In this way, we make VLP light-weight enough even for resource-constrained wearable devices, e.g. smart glasses. Moreover, the polarization-based VLC can be applied to any illuminating light sources, thereby eliminating the dependency on LED. This paper presents the VLP system PIXEL, which realizes our idea. In PIXEL, we develop three techniques, each of which addresses a design challenge: 1) a novel color-based modulation scheme to handle users? mobility, 2) an adaptive downsampling algorithm to tackle the uneven sampling problem of wearables? low-cost camera and 3) a computational optimization method for the positioning algorithm to enable real-time processing. We implement PIXEL?s hardware using commodity components and develop a software program for both smartphone and Google glass. Our experiments based on the prototype show that PIXEL can provide accurate realtime VLP for wearables and smartphones with camera resolution as coarse as 60 pixel x 80 pixel and CPU frequency as low as 300MHz.

https://yangzhice.com/docforweb/PIXEL/PIXEL_Mobisys.pdf

Wearables Can Afford: Light-weight Indoor Positioning with Visible Light

Emerging communication network applications including fifth-generation (5G) cellular and the Internet-of-Things (IoT) will almost certainly require location information at as many network nodes as possible. Given the energy requirements and lack of indoor coverage of Global Positioning System (GPS), collaborative localization appears to be a powerful tool for such networks. In this paper, we survey the state of the art in collaborative localization with an eye toward 5G cellular and IoT applications. In particular, we discuss theoretical limits, algorithms, and practical challenges associated with collaborative localization based on range-based as well as range-angle-based techniques.

https://research.chalmers.se/publication/503903/file/503903_Fulltext.pdf

Collaborative Sensor Network Localization: Algorithms and Practical Issues

Virtualization has been seen as one of the main evolution trends in the forthcoming fifth generation (5G) cellular networks which enables the decoupling of infrastructure from the services it provides. In this case, the roles of infrastructure providers (InPs) and mobile virtual network operators (MVNOs) can be logically separated and the resources (e.g., subchannels, power, and antennas) of a base station owned by an InP can be transparently shared by multiple MVNOs, while each MVNO virtually owns the entire BS. Naturally, the issue of resource allocation arises. In particular, the InP is required to abstract the physical resources into isolated slices for each MVNO who then allocates the resources within the slice to its subscribed users. In this paper, we aim to address this two-level hierarchical resource allocation problem while satisfying the requirements of efficient resource allocation, strict inter-slice isolation, and the ability of intra-slice customization. To this end, we design a hierarchical combinatorial auction mechanism, based on which a truthful and sub-efficient resource allocation framework is provided. Specifically, winner determination problems (WDPs) are formulated for the InP and MVNOs, and computationally tractable algorithms are proposed to solve these WDPs. Also, pricing schemes are designed to ensure incentive compatibility. The designed mechanism can achieve social efficiency in each level even if each party involved acts selfishly. Numerical results show the effectiveness of the proposed scheme.

Virtualization of 5G Cellular Networks as a Hierarchical Combinatorial Auction

Auction is widely applied in wireless communication for spectrum allocation. Most of prior works have assumed that all spectrums are identical. In reality, however, spectrums provided by different owners have distinctive characteristics in both spacial and frequency domains. Spectrum availability also varies in different geo-locations. Furthermore, frequency diversity may cause non-identical conflict relationships among spectrum buyers since different frequencies have distinct communication ranges. Under such a scenario, existing spectrum auction schemes cannot provide truthfulness or efficiency. In this paper, we propose a Truthful double Auction mechanism for HEterogeneous Spectrum, called TAHES, which allows buyers to explicitly express their personalized preferences for heterogeneous spectrums and also addresses the problem of interference graph variation. We prove that TAHES has nice economic properties including truthfulness, individual rationality and budget balance. Results from extensive simulation studies demonstrate the truthfulness, effectiveness and efficiency of TAHES.

TAHES: A Truthful Double Auction Mechanism for Heterogeneous Spectrums

According to the FCC's final rule for the unlicensed use of TV white spaces, secondary users are required to query a geo-location database to determine whether a spectrum band is occupied or not. However, how to design a multi-cell infrastructure-based secondary network to dynamically access TV white spaces with the help of database is still an open issue. In this paper, we present the design and implementation of WhiteNet, a multi-cell infrastructure-based dynamic spectrum access system on TV white spaces. WhiteNet is compatible with the FCC's database architecture. In WhiteNet, the geo-location database is exploited to assist multi-AP coordination. A low-overhead distributed spectrum allocation algorithm is proposed to allocate spectrum among multiple APs in WhiteNet, considering the heterogeneous propagation property among various spectrum bands throughout TV white spaces. A novel AP discovery scheme is designed to enable users to discover and select the best access point to connect. We implement WhiteNet in a 7-node GNU Radio testbed, which demonstrates the feasibility of our system. Evaluation results show that our spectrum allocation algorithm can significantly increase total network throughput, besides, the AP discovery scheme is reliable and efficient.

Database-assisted multi-AP network on TV white spaces: Architecture, spectrum allocation and AP discovery

Auction is widely applied in wireless communication for spectrum allocation. Most of prior works have assumed that spectrums are identical. In reality, however, spectrums provided by different owners have distinctive characteristics in both spacial and frequency domains. Spectrum availability also varies in different geo-locations. Furthermore, frequency diversity may cause non-identical conflicts among spectrum buyers since different frequencies have distinct communication ranges. Under such realistic scenario, existing spectrum auction schemes cannot provide truthfulness or efficiency. In this paper, we propose a Truthful double Auction for HEterogeneous Spectrum, called TAHES. TAHES allows buyers to explicitly express their personalized preferences for heterogeneous spectrums and also addresses the problem of interference graph variation. We prove that TAHES has nice economic properties including truthfulness, individual rationality and budget balance.

/pdf/tahes-truthful-double-auction-for-heterogeneous-spectrums-2utfol01h3.pdf

TAHES: Truthful double Auction for Heterogeneous Spectrums

Spectrum auction is widely applied in spectrum redistributions, especially under the dynamic spectrum management context. However, due to the high price asked by the spectrum holders, secondary users (SUs) with limited budget cannot benefit from such auction directly. Motivated by the recent group-buying behaviors in the Internet based service, we advocate that SUs can be grouped together to take part in the spectrum auction as a whole to increase their chances to win the channel. The cost and benefit of the won spectrum are then shared evenly among the SUs within the group. None of the existing auction models can be applied in this scenario due to three unique challenges: how can a group leader select the winning SUs and charge them fairly and efficiently; how to guarantee truthfulness of users' bids; how to match the heterogeneous channels to groups when one group would like to buy at most one channel. In this paper, we propose TASG, a Three-stage Auction framework for Spectrum Group-buying to address the above challenges and enable group-buying behaviors among SUs. In the first stage, we propose an algorithm to decide the group members and bids for the channels. In the second stage, we conduct auction between the group leaders and the spectrum holder, with a novel winner determination algorithm. In the third stage, the group leaders further distribute spectrum and bills to the SUs in the group. TASG possesses good properties such as truthfulness, individual rationality, improved system efficiency, and computational tractability.

Groupon in the Air: A three-stage auction framework for Spectrum Group-buying

The promise of high speed (over 1Gbps) wireless transmission rate at the physical layer can be significantly compromised with the current design of 802.11 DCF. There are three overheads in the 802.11 MAC that contribute to the performance degradation: DIFS, random backoff and ACK. Motivated by the recent progress in OFDM and self-interference cancellation technologies, in this paper, we propose a novel MAC design called REPICK (REversed contention and PIggy-backed ACK) to collectively address all the three overheads. The key idea in our proposal is to take advantage of OFDM subcarriers in the frequency domain to enhance the MAC efficiency. In REPICK, we propose a novel reverse contention algorithm, which enables and facilitates receivers to contend channel in the frequency domain (reversed contention). We also design an efficient mechanism which allows ACKs from receivers to be piggy-backed through subcarriers together with the contention information (piggy-backed ACK). We prove through rigorous analysis that the proposed scheme can substantially reduce the overheads associated with 802.11 DCF and a guaranteed throughput gain can be obtained. In addition, results from extensive simulations demonstrate that REPICK can improve the throughput by up to 170%.

/pdf/use-your-frequency-wisely-explore-frequency-domain-for-3eiwtooba4.pdf

Xiaojun Feng

Papers

TAHES: A Truthful Double Auction Mechanism for Heterogeneous Spectrums

Database-assisted multi-AP network on TV white spaces: Architecture, spectrum allocation and AP discovery

TAHES: Truthful double Auction for Heterogeneous Spectrums

Groupon in the Air: A three-stage auction framework for Spectrum Group-buying

Use your frequency wisely: Explore frequency domain for channel contention and ACK