In secondary spectrum trading markets, auctions are widely used by spectrum holders (SHs) to redistribute their unused channels to secondary wireless service providers (WSPs). As sellers, the SHs design proper auction schemes to stimulate more participants and to maximize the revenue from the auction. As buyers, the WSPs determine the bidding strategies in the auction to better serve their end users. In this paper, we consider a three-layered spectrum trading market consisting of the SH, the WSPs, and the end users. We jointly study the strategies of the three parties. The SH determines the auction scheme and spectrum supplies to optimize its revenue. The WSPs have flexible bidding strategies in terms of both demands and valuations considering the strategies of the end users. For this market, we design a novel auction mechanism called FlexAuc to enable dynamic supplies and demands in the auction. We theoretically prove that FlexAuc not only maximizes the social welfare but also preserves other nice properties such as truthfulness and computational tractability.

In spectrum trading markets, auctions are organized by spectrum holders (SHs) to distribute channels. As buyers, wireless service providers (WSPs) acquire channels to deploy services to end users. To optimize the profits, it is essential for the WSPs to determine their bidding strategies, which are affected by two key aspects: the service position to the end users and the auction schemes enforced by the SH. In this paper, we jointly study the strategy of the SH in the auction design and the WSPs' strategies in the service provisions and biddings. The WSP's optimal strategy in the auction can be flexible in term of demands and valuations. To optimize social welfare and enable the WSPs to reveal truthful flexible demands, we design Flexauc, a novel auction mechanism for the SH. We prove theoretically that Flexauc not only maximizes the social welfare but also preserves other nice properties: truthfulness and computational tractability.

Existing work on indoor localization achieves accuracy by conducting site surveys or deploying additional infrastructures. In this paper, we study the feasibility of designing a low cost scheme, which is based on pedestrian dead reckoning and free from these requirements. Our method targets the scenarios where there are a large number of pedestrians in the public places holding their mobile phones while walking. First, we make one key observation that positioning errors brought by different pedestrians are diverse and can be mutually compensated. Second, we leverage the acoustic communication ability in mobile phone to enable users to exchange their locations when they meet with each other within a short distance. The received location information is crowdsourced to get a better location estimate. Finally, we use extensive experiments to evaluate the proposed scheme; the experiments are conducted in a 3,500 square-meter area with more than 18 hours (more than 100 km) real walking traces. Results show that our method is able to reduce the median localization error to 4 m when the user density of the area is more than 50/3,500 per square-meter.

According to the recent rulings of the Federal Communications Commission (FCC), TV white spaces (TVWS) can now be accessed by secondary users (SUs) after a list of vacant TV channels is obtained via a geo-location database. Proper business models are therefore essential for database operators to manage geo-location databases. Database access can be simultaneously priced under two different schemes: the registration scheme and the service plan scheme. In the registration scheme, the database reserves part of the TV bandwidth for registered White Space Devices (WSDs). In the service plan scheme, the WSDs are charged according to their queries. In this paper, we investigate the business model for the TVWS database under a hybrid pricing scheme. We consider the scenario where a database operator employs both the registration scheme and the service plan scheme to serve the SUs. The SUs' choices of different pricing schemes are modeled as a non-cooperative game and we derive distributed algorithms to achieve Nash Equilibrium (NE). Considering the NE of the SUs, the database operator optimally determines pricing parameters for both pricing schemes in terms of bandwidth reservation, registration fee and query plans.

In this paper, we investigate the coexistence problem between the 802.22 and the 802.11af systems in the TV White Spaces (TVWS). We focus on the design of a co-channel coexistence scheme for the 802.22 customer-premises equipments (CPE) and the 802.11af systems. 802.22 and 802.11af are two typical standards envisioned to be widely adopted in the future. However, these two standards are heterogeneous in both power level and PHY/MAC design, making their coexistence challenging. To avoid mutual interference between the two systems, existing solutions have to allocate different channels for the two networks. Due to the city-wide coverage of the 802.22 base station (BS), the spectrum utilization is compromised with existing schemes. In this paper, we first identify the challenges to enable the co-channel coexistence of the 802.22 and the 802.11af systems and then propose a busy-tone based framework. We design a busy-tone for the 802.22 CPEs to exclude the hidden 802.11af terminals. We also show that it is possible for the 802.11af systems to identify the exposed 802.22 CPE transmitters and conduct successful transmissions under interference. We show through extensive simulations that the spectrum utilization can be increased with the proposed co-channel coexistence scheme.

In this paper, we consider the scenario where a secondary operator leases licensed spectrum from a spectrum owner and then serves its end users with both licensed and unlicensed bands. An end user can decide its traffic segmentation in terms of the percentage of its total amount of traffic demand transmitted via licensed and unlicensed band respectively. The optimal spectrum investment and pricing decision of the secondary operator is studied considering the user-determined traffic segmentation. We model and analyze the interactions among the spectrum owner, the secondary operator and the end users with Stackelberg game. By deriving optimal strategies for the three types of game players, we show that the end users can increase their utility by determining a proper traffic segmentation on the licensed and unlicensed band considering both the service price and the quality of service (QoS). Also the secondary operator and the spectrum owner can make more profit leveraging dynamic spectrum leasing.

According to the recent rulings of the Federal Communications Commission (FCC), TV white spaces (TVWS) can now be accessed by secondary users (SUs) after a list of vacant TV channels is obtained via a geo-location database. Proper business models are essential for database operators to manage the cost of maintaining geo-location databases. Database access can be simultaneously priced under two different schemes: the registration scheme and the service plan scheme. In the registration scheme, the database reserves part of the TV bandwidth for registered White Space Devices (WSD) in a soft-license way. In the service plan scheme, WSDs are charged according to their queries. In this paper, we investigate the business model for the TVWS database under a hybrid pricing scheme. We consider the scenario where a database operator employs both the registration scheme and the service plan scheme to serve the SUs. The SUs' choices of different pricing schemes are modeled as a non-cooperative game and we derive distributed algorithms to achieve the Nash Equilibrium (NE). Considering the NE of the SUs, the database operator optimally determines the pricing parameters for both pricing schemes in terms of bandwidth reservation, registration fee and query plans.

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.

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.

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%.

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.

The promise of high speed (over 1Gbps) wireless transmission rate at the physical layer can be significantly compromised with the current design in 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 current progress in OFDM and self-interference cancellation technologies, in this poster, we propose a novel MAC design called REPICK (REversed contention and PIggy-backed ACK) to collectively address these problems. The key idea in our proposal is to take advantage of OFDM subcarriers in the frequency domain to enhance the MAC efficiency. Specifically, in REPICK, we propose a novel reverse contention algorithm which enables receivers to contend for channel access with subcarriers in the frequency domain (reversed contention). We also design a mechanism which allows ACKs from receivers to be piggy-backed through subcarriers together with the contention information (piggy-backed ACK). We demonstrate REPICK's efficiency through both analysis and simulations.

Vehicular Ad-hoc Networks(VANETs) can facilitate many applications such as road safety, intelligent transportation and advertising. These applications usually call for multi-hop data delivery from access points to moving vehicles with user specified delay requirements. However, most existing routing protocols for VANETs only focus on message forwarding from vehicles to access points or take no account of the delay constraint. In this paper, we focus on the development of a carry-and-forward scheme that delivers data from access points to vehicles. Utilizing the vehicle's trajectory obtained from the navigation system, we propose TaDB, a Trajectory-assisted Delay Bounded Message Delivery Algorithm. To choose delivery route within delay constraint while minimizing transmission cost, TaDB uses a Cluster-Aware Link Delay Model to estimate link delay for both the Carry and the Forward strategies on each road segment. TaDB also leverages the vehicle's planned trajectory to estimate its future location. Simulation results show that TaDB can achieve a delivery ratio very close to optimal.

In this paper, we propose an adaptive interpolation method for low quality still images such as single video frames. Our method chooses different interpolation schemes according to the local image context. First, we segment the image into three types of regions: smooth regions which contain no edges, well-defined edges such as object boundaries, and textured regions which are covered by dense spurious edges. For smooth regions, we simply apply bilinear interpolation. For the well-defined edges, we develop an edge-directed interpolation scheme. For the remaining textured regions, we apply a residual error estimation method to enhance the high frequency components, hence improving the visual sharpness of these regions. Our results show a visible improvement compared to images generated by traditional interpolation methods, with sharp edges, enhanced textures, and low noise level in smooth regions.