Jianqing Liu

A Privacy-Preserving Networked Hospitality Service with the Bitcoin Blockchain

In recent years, we have witnessed a rise in the popularity of networked hospitality services (NHSs), an online marketplace for short-term peer-to-peer accommodations. Such systems, however, raise significant privacy concerns, because service providers such as Airbnb and 9flats can easily collect the precise and personal information of millions of participating hosts and guests through their centralized online platforms. In this paper, we propose PrivateNH, a privacy-enhancing and practical solution that offers anonymity and accountability for NHS users without relying on any trusted third party. PrivateNH leverages the recent progress of Bitcoin techniques such as Colored Coins and CoinShuffle to generate and maintain anonymous credentials for NHS participants. The credential holders (NHS hosts or guests) can then lease or rent short-term lodging and interact with the service provider in an anonymous and accountable manner. An anonymous and secure reputation system is also introduced to establish the trust between unfamiliar hosts and guests in a peer-to-peer fashion. The proposed scheme is compatible with the current Bitcoin blockchain system, and its effectiveness and feasibility in NHS scenario are also demonstrated by security analysis and performance evaluation.

Data and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network Architecture

Future wireless networks will progressively displace service provisioning towards the edge to accommodate increasing growth in traffic. This paradigm shift calls for smart policies to efficiently share network resources and ensure service delivery. In this paper, we consider a cognitive dynamic network architecture (CDNA) where primary users (PUs) are rewarded for sharing their connectivities and acting as access points for secondary users (SUs). CDNA creates opportunities for capacity increase by network-wide harvesting of unused data plans and spectrum from different operators. Different policies for data and spectrum trading are presented based on centralized, hybrid, and distributed schemes involving primary operator (PO), secondary operator (SO), and their respective end users. In these schemes, PO and SO progressively delegate trading to their end users and adopt more flexible cooperation agreements to reduce computational time and track available resources dynamically. A novel matching-with-pricing algorithm is presented to enable self-organized SU-PU associations, channel allocation and pricing for data and spectrum with low computational complexity. Since connectivity is provided by the actual users, the success of the underlying collaborative market relies on the trustworthiness of the connections. A behavioral-based access control mechanism is developed to incentivize/penalize honest/dishonest behavior and create a trusted collaborative network. Numerical results show that the computational time of the hybrid scheme is one order of magnitude faster than the benchmark centralized scheme and that the matching algorithm reconfigures the network up to three orders of magnitude faster than in the centralized scheme.

Communication through Symbol Silence: Towards Free Control Messages in Indoor WLANs

Efficient design of wireless networks benefits from the exchange of control messages. However, control messageitself consumes scarce channel resources. In this paper, wepropose CoS (Communication through symbol Silence), a novel communication strategy that conveys control messages for free without consuming extra channel resources. CoS inserts silence symbols in data packets and leverages the intervals between inserted silence symbols to encode information. The silence symbols can be located by energy detection at the granularity of symbols and the intervals are interpreted into transmittedcontrol messages. Based on our key insights that the channel code is under-utilized in current wireless networks and the distribution of symbol errors within a data packet is predictable in indoor wireless transmissions, the symbols erased by silence symbols are recovered by the coding redundancy that is originally used to correct symbol errors. A rate adaptation scheme is designed to dynamically adjust the rate of free control messages according to channel conditions so that the transmission of free control messages does not harm the original data throughput. We implement CoS on our software defined radio platform to validate the feasibility of CoS. The extensive results show that the control messages are delivered with close to 100% accuracy in a large SNR range. In addition, we measure the achievable capacity of free control messages in various channel conditions.

Energy-Efficient Secondary Traffic Scheduling with MIMO Beamforming

When equipped with multiple antennas, secondary users in cognitive radio networks are able to communicate even when neighboring primary users are active by transmitting in the null space of the communication channel occupied by primary users. In this case, the throughput of a secondary link is limited by the transmission power and the dimension of the null space, i.e., the number of active primary users nearby. Since the number of active primary users is time-varying, the required transmission power to support certain data rate changes from time to time. Thus, secondary users could adapt their transmission to the variation of the primary traffic to improve energy efficiency. In view of that, we develop an energy-efficient traffic scheduling scheme for secondary users equipped with multiple antennas. By formulating the traffic scheduling problem as a Markov decision problem, an energy-efficient transmission scheme is derived from linear programming. The analytical results are verified by simulations and the impacts of various parameters are discussed. The superiority of the derived scheme is also shown by comparing with a randomized scheme.