arXiv subjects

Lingjie Duan

Publications and source records attributed to Lingjie Duan.

At least 91 records · Page 5Linked to original sources

arXiv2017

Proactive Eavesdropping via Cognitive Jamming in Fading Channels

To enhance the national security, there is a growing need for government agencies to legitimately monitor suspicious communication links for preventing intended crimes and terror attacks. In this paper, we propose a new wireless information surveillance paradigm by investigating a scenario where a legitimate monitor aims to intercept a suspicious wireless communication link over fading channels. The legitimate monitor can successfully eavesdrop (decode) the information of the suspicious link at each fading state only when its achievable data rate is no smaller than that at the suspicious receiver. In practice, such legitimate eavesdropping is particularly challenging, since the legitimate monitor may be far away from the suspicious transmitter and cannot eavesdrop efficiently. To overcome this issue, we propose a new approach, namely proactive eavesdropping via cognitive jamming, in which the legitimate monitor purposely jams the receiver so as to change the suspicious communication (e.g., to a smaller data rate) for overhearing more efficiently. In particular, we consider delay-sensitive and delay-tolerant applications for the suspicious data communications, under which the legitimate monitor maximizes the eavesdropping non-outage probability for event-based monitoring and the relative eavesdropping rate for content analysis, respectively, by optimizing its jamming power allocation over different fading states subject to an average power constraint. Numerical results show that the proposed proactive eavesdropping via cognitive jamming approach greatly outperforms the conventional passive eavesdropping without jamming and the proactive eavesdropping with constant-power jamming.

cs.IT↗

arXiv2016

Fundamental Rate Limits of Physical Layer Spoofing

This letter studies an emerging wireless communication intervention problem at the physical layer, where a legitimate spoofer aims to spoof a malicious link from Alice to Bob, by replacing Alice's transmitted source message with its target message at Bob side. From an information-theoretic perspective, we are interested in characterizing the maximum achievable spoofing rate of this new spoofing channel, which is equivalent to the maximum achievable rate of the target message at Bob, under the condition that Bob cannot decode the source message from Alice. We propose a novel combined spoofing approach, where the spoofer sends its own target message, combined with a processed version of the source message to cancel the source message at Bob. For both cases when Bob treats interference as noise (TIN) or applies successive interference cancelation (SIC), we obtain the maximum achievable spoofing rates by optimizing the power allocation between the target and source messages at the spoofer.

cs.IT↗

arXiv2016

Surveillance and Intervention of Infrastructure-Free Mobile Communications: A New Wireless Security Paradigm

Conventional wireless security assumes wireless communications are rightful and aims to protect them against malicious eavesdropping and jamming attacks. However, emerging infrastructure-free mobile communication networks are likely to be illegally used (e.g., by criminals or terrorists) but difficult to be monitored, thus imposing new challenges on the public security. To tackle this issue, this article presents a paradigm shift of wireless security to the surveillance and intervention of infrastructure-free suspicious and malicious wireless communications, by exploiting legitimate eavesdropping and jamming jointly. In particular, {\emph{proactive eavesdropping}} (via jamming) is proposed to intercept and decode information from suspicious communication links for the purpose of inferring their intentions and deciding further measures against them. {\emph{Cognitive jamming}} (via eavesdropping) is also proposed so as to disrupt, disable, and even spoof the targeted malicious wireless communications to achieve various intervention tasks.

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arXiv2016

Cooperative Local Caching under Heterogeneous File Preferences

Local caching is an effective scheme for leveraging the memory of the mobile terminal (MT) and short range communications to save the bandwidth usage and reduce the download delay in the cellular communication system. Specifically, the MTs first cache in their local memories in off-peak hours and then exchange the requested files with each other in the vicinity during peak hours. However, prior works largely overlook MTs' heterogeneity in file preferences and their selfish behaviours. In this paper, we practically categorize the MTs into different interest groups according to the MTs' preferences. Each group of MTs aims to increase the probability of successful file discovery from the neighbouring MTs (from the same or different groups). Hence, we define the groups' utilities as the probability of successfully discovering the file in the neighbouring MTs, which should be maximized by deciding the caching strategies of different groups. By modelling MTs' mobilities as homogeneous Poisson point processes (HPPPs), we analytically characterize MTs' utilities in closed-form. We first consider the fully cooperative case where a centralizer helps all groups to make caching decisions. We formulate the problem as a weighted-sum utility maximization problem, through which the maximum utility trade-offs of different groups are characterized. Next, we study two benchmark cases under selfish caching, namely, partial and no cooperation, with and without inter-group file sharing, respectively. The optimal caching distributions for these two cases are derived. Finally, numerical examples are presented to compare the utilities under different cases and show the effectiveness of the fully cooperative local caching compared to the two benchmark cases.

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arXiv2016

Dynamic routing for social information sharing

Today mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths despite the potentially higher costs associated with their trips. In this paper we combine the benefits from social information sharing with the fundamental routing problem where a unit mass of non-atomic selfish users decide their trips in a non-cooperative game by choosing between a high-cost and a low-cost path. To remedy the inefficient low-content equilibrium where all users choose to explore a single path (the low-cost path), we propose and analyse two new incentive mechanisms that can be used by the social network application, one based on side payments and the other on restricting access to content for users that choose the low cost path. We also obtain interesting price of anarchy results that show some fundamental tradeoffs between achieving path diversity and maintaining greater user participation, motivating a combined mechanism to further increase the social welfare. Our model extends classical dynamic routing in the case of externalities caused from traffic on different paths of the network.

cs.GT↗

arXiv2016

Transmit Optimization for Symbol-Level Spoofing

With recent developments of wireless communication technologies, malicious users can use them to commit crimes or launch terror attacks, thus imposing new threats on the public security. To quickly respond to defend these attacks, authorized parities (e.g., the National Security Agency of the USA) need to intervene in the malicious communication links over the air. This paper investigates this emerging wireless communication intervention problem at the physical layer. Unlike prior studies using jamming to disrupt or disable the targeted wireless communications, we propose a new physical-layer spoofing approach to change their communicated information. Consider a fundamental three-node system over additive white Gaussian noise (AWGN) channels, in which an intermediary legitimate spoofer aims to spoof a malicious communication link from Alice to Bob, such that the received message at Bob is changed from Alice's originally sent message to the one desired by the spoofer. We propose a new symbol-level spoofing scheme, where the spoofer designs the spoofing signal via exploiting the symbol-level relationship between each original constellation point of Alice and the desirable one of the spoofer. In particular, the spoofer aims to minimize the average spoofing-symbol-error-rate (SSER), which is defined as the average probability that the symbols decoded by Bob fail to be changed or spoofed, by designing its spoofing signals over symbols subject to the average transmit power constraint. By considering two cases when Alice employs the widely-used binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK) modulations, we obtain the respective optimal solutions to the two average SSER minimization problems. Numerical results show that the symbol-level spoofing scheme with optimized transmission achieves a much lower average SSER, as compared to other benchmark schemes.

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arXiv2016

Harnessing Self-Interference in Full-Duplex Relaying: An Analog Filter-and-Forward Approach

This paper studies a full-duplex filter-and-forward (FD-FF) relay system in frequency-selective channels. Conventionally, the loop-back signal at the FD relay is treated as harmful self-interference and needs to be significantly suppressed via both analog- and digital-domain cancellation. However, the performance of the conventional self-interference cancellation approach is fundamentally limited due to the quantization error induced by the analog-to-digital converter (ADC) with limited dynamic range. In this paper, we consider an analog filter-and-forward design to help avoid the quantization error, and surprisingly show that the maximum achievable rate of such an FD-FF relay system is in fact regardless of the loop-back channel at the FD relay. We characterize the maximum achievable rate of this channel by jointly optimizing the transmit power allocation over frequency at the source and the frequency response of the filter at the relay, subject to their individual power constraints. Although this problem is non-convex, we obtain its optimal solution by applying the Lagrange duality method. By simulations it is shown that the proposed joint source and relay optimization achieves rate gains over other heuristic designs, and is also advantageous over the conventional approach by cancelling the relay loop-back signal as self-interference, especially when the residual self-interference after cancellation is still significant.

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arXiv2016

To Motivate Social Grouping in Wireless Networks

We consider a group of neighboring smartphone users who are roughly at the same time interested in the same network content, called common interests. However, ever-increasing data traffic challenges the limited capacity of base-stations (BSs) in wireless networks. To better utilize the limited BSs' resources under unreliable wireless networks, we propose local common-interests sharing (enabled by D2D communications) by motivating the physically neighboring users to form a social group. As users are selfish in practice, an incentive mechanism is needed to motivate social grouping. We propose a novel concept of equal-reciprocal incentive over broadcast communications, which fairly ensures that each pair of the users in the social group share the same amount of content with each other. As the equal-reciprocal incentive may restrict the amount of content shared among the users, we analyze the optimal equal-reciprocal scheme that maximizes local sharing content. While ensuring fairness among users, we show that this optimized scheme also maximizes each user's utility in the social group. Finally, we look at dynamic content arrivals and extend our scheme successfully by proposing novel on-line scheduling algorithms.

cs.SI↗

arXiv2016

Two-sided Matching Based Cooperative Spectrum Sharing

Dynamic spectrum access (DSA) can effectively improve the spectrum efficiency and alleviate the spectrum scarcity, by allowing unlicensed secondary users (SUs) to access the licensed spectrum of primary users (PUs) opportunistically. Cooperative spectrum sharing is a new promising paradigm to provide necessary incentives for both PUs and SUs in dynamic spectrum access. The key idea is that SUs relay the traffic of PUs in exchange for the access time on the PUs' licensed spectrum. In this paper, we formulate the cooperative spectrum sharing between multiple PUs and multiple SUs as a two-sided market, and study the market equilibrium under both complete and incomplete information. First, we characterize the sufficient and necessary conditions for the market equilibrium. We analytically show that there may exist multiple market equilibria, among which there is always a unique Pareto-optimal equilibrium for PUs (called PU-Optimal-EQ), in which every PU achieves a utility no worse than in any other equilibrium. Then, we show that under complete information, the unique Pareto-optimal equilibrium PU-Optimal-EQ can always be achieved despite the competition among PUs; whereas, under incomplete information, the PU-Optimal-EQ may not be achieved due to the mis-representations of SUs (in reporting their private information). Regarding this, we further study the worse-case equilibrium for PUs, and characterize a Robust equilibrium for PUs (called PU-Robust-EQ), which provides every PU a guaranteed utility under all possible mis-representation behaviors of SUs. Numerical results show that in a typical network where the number of PUs and SUs are different, the performance gap between PU-Optimal-EQ and PU-Robust-EQ is quite small (e.g., less than 10% in the simulations).

cs.GT↗

arXiv2016

Optimal Pricing and Admission Control for Heterogeneous Secondary Users

This paper studies how to maximize a spectrum database operator's expected revenue in sharing spectrum to secondary users, through joint pricing and admission control of spectrum resources. A unique feature of our model is the consideration of the stochastic and heterogeneous nature of secondary users' demands. We formulate the problem as a stochastic dynamic programming problem, and present the optimal solutions under both static and dynamic pricing schemes. In the case of static pricing, the prices do not change with time, although the admission control policy can still be time-dependent. In this case, we show that a stationary (time-independent) admission policy is in fact optimal under a wide range of system parameters. In the case of dynamic pricing, we allow both prices and admission control policies to be time-dependent. We show that the optimal dynamic pricing can improve the operator's revenue by more than 30% over the optimal static pricing, when secondary users' demands for spectrum opportunities are highly elastic.

cs.NI↗

arXiv2016

Green 5G Heterogeneous Networks through Dynamic Small-Cell Operation

Traditional macro-cell networks are experiencing an upsurge of data traffic, and small-cells are deployed to help offload the traffic from macro-cells. Given the massive deployment of small-cells in a macro-cell, the aggregate power consumption of small-cells (though being low individually) can be larger than that of the macro-cell. Compared to the macro-cell base station (MBS) whose power consumption increases significantly with its traffic load, the power consumption of a small-cell base station (SBS) is relatively flat and independent of its load. To reduce the total power consumption of the heterogeneous networks (HetNets), we dynamically change the operating states (on and off) of the SBSs, while keeping the MBS on to avoid any service failure outside active small-cells. First, we consider that the wireless users are uniformly distributed in the network, and propose an optimal location-based operation scheme by gradually turning off the SBSs closer to the MBS. We then extend the operation problem to a more general case where users are non-uniformly distributed in the network. Although this problem is NP-hard, we propose a joint location and user density based operation scheme to achieve near-optimum (with less than 1\% performance loss in our simulations) in polynomial time.

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arXiv2015

Dynamic Base Station Operation in Large-Scale Green Cellular Networks

In this paper, to minimize the on-grid energy cost in a large-scale green cellular network, we jointly design the optimal base station (BS) on/off operation policy and the on-grid energy purchase policy from a network-level perspective. Due to the fluctuations of the on-grid energy prices, the harvested renewable energy, and the network traffic loads over time, as well as the BS coordination to hand over the traffic offloaded from the inactive BSs to the active BSs, it is generally NP-hard to find a network-level optimal adaptation policy that can minimize the on-grid energy cost over a long-term and yet assures the downlink transmission quality at the same time. Aiming at the network-level dynamic system design, we jointly apply stochastic geometry (Geo) for large-scale green cellular network analysis and dynamic programming (DP) for adaptive BS on/off operation design and on-grid energy purchase design, and thus propose a new Geo-DP design approach. By this approach, we obtain the optimal BS on/off policy, which shows that the optimal BSs' active operation probability in each horizon is just sufficient to assure the required downlink transmission quality with time-varying load in the large-scale cellular network. We also propose a suboptimal on-grid energy purchase policy with low-complexity, where the low-price on-grid energy is over-purchased in the current horizon only when the current storage level and the future renewable energy level are both low. We compare the proposed policy with the existing schemes and show that our proposed policy can more efficiently save the on-grid energy cost over time.

cs.IT↗

arXiv2015

Energy Group-Buying with Loading Sharing for Green Cellular Networks

In the emerging hybrid electricity market, mobile network operators (MNOs) of cellular networks can make day-ahead energy purchase commitments at low prices and real-time flexible energy purchase at high prices. To minimize electricity bills, it is essential for MNOs to jointly optimize the day-ahead and real-time energy purchase based on their time-varying wireless traffic load. In this paper, we consider two different MNOs coexisting in the same area, and exploit their collaboration in both energy purchase and wireless load sharing for energy cost saving. Specifically, we propose a new approach named energy group buying with load sharing, in which the two MNOs are aggregated as a single group to make the day-ahead and real-time energy purchase, and their base stations (BSs) share the wireless traffic to maximally turn lightly-loaded BSs into sleep mode. When the two MNOs belong to the same entity and aim to minimize their total energy cost, we use the two-stage stochastic programming to obtain the optimal day-ahead and real-time energy group buying jointly with wireless load sharing. When the two MNOs belong to different entities and are self-interested in minimizing their individual energy costs, we propose a novel repeated Nash bargaining scheme for them to negotiate and share their energy costs under energy group buying and load sharing. Our proposed repeated Nash bargaining scheme is shown to achieve Pareto-optimal and fair energy cost reductions for both MNOs.

cs.IT↗

arXiv2015

Proactive Eavesdropping via Jamming for Rate Maximization over Rayleigh Fading Channels

Instead of against eavesdropping, this letter proposes a new paradigm in wireless security by studying how a legitimate monitor (e.g., government agencies) efficiently eavesdrops a suspicious wireless communication link. The suspicious transmitter controls its communication rate over Rayleigh fading channels to maintain a target outage probability at the receiver, and the legitimate monitor can successfully eavesdrop only when its achievable rate is no smaller than the suspicious communication rate. We propose a proactive eavesdropping via jamming approach to maximize the average eavesdropping rate, where the legitimate monitor sends jamming signals with optimized power control to moderate the suspicious communication rate.

cs.IT↗

arXiv2015

Multi-antenna Wireless Powered Communication with Co-channel Energy and Information Transfer

This letter studies a multi-antenna wireless powered communication (WPC) system with co-channel energy and information transfer, where a wireless device (WD), powered up by wireless energy transfer (WET) from an energy transmitter (ET), communicates to an information receiver (IR) over the same frequency band. We maximize the achievable data rate from the WD to the IR by jointly optimizing the energy beamforming at the ET and the information beamforming at the WD, subject to their individual transmit power constraints. We obtain the optimal solution to this problem in closed-form, where the optimal energy beamforming at the ET achieves a best energy/interference tradeoff between maximizing the energy transfer efficiency to the WD and minimizing the co-channel interference to the IR. Numerical results show that our proposed optimal co-channel design is superior to other reference schemes.

cs.IT↗

arXiv2015

Adaptively Directional Wireless Power Transfer for Large-scale Sensor Networks

Wireless power transfer (WPT) prolongs the lifetime of wireless sensor network by providing sustainable power supply to the distributed sensor nodes (SNs) via electromagnetic waves. To improve the energy transfer efficiency in a large WPT system, this paper proposes an adaptively directional WPT (AD-WPT) scheme, where the power beacons (PBs) adapt the energy beamforming strategy to SNs' locations by concentrating the transmit power on the nearby SNs within the efficient charging radius. With the aid of stochastic geometry, we derive the closed-form expressions of the distribution metrics of the aggregate received power at a typical SN and further approximate the complementary cumulative distribution function using Gamma distribution with second-order moment matching. To design the charging radius for the optimal AD-WPT operation, we exploit the tradeoff between the power intensity of the energy beams and the number of SNs to be charged. Depending on different SN task requirements, the optimal AD-WPT can maximize the average received power or the active probability of the SNs, respectively. It is shown that both the maximized average received power and the maximized sensor active probability increase with the increased deployment density and transmit power of the PBs, and decrease with the increased density of the SNs and the energy beamwidth. Finally, we show that the optimal AD-WPT can significantly improve the energy transfer efficiency compared with the traditional omnidirectional WPT.

cs.IT↗

arXiv2015

Optimal Pricing and Load Sharing for Energy Saving in Communications Cooperation

In this paper, we propose a pricing mechanism for the uplink communication cooperation to save the energy of mobile terminals (MTs) in wireless cellular network. Under the uncertainties of the other MTs' channel and battery conditions, a source MT in low battery level or bad channel condition is allowed to select and pay another MT in proximity to help forward its data package to the base station (BS). We formulate the source MT's pricing and load sharing problem as an optimization problem to minimize its expected energy cost. When the source MT cannot split its data package for a certain multimedia application, we motivate the selected relay MT to forward the whole data package by obtaining the optimal pricing through a dichotomous search algorithm. When the source MT can split the data package, we jointly optimize the pricing and load sharing with the relay MT and propose an alternating optimization algorithm that achieves near-optimal solution. Extensive numerical results are provided to show that our proposed pricing mechanism can significantly decrease the source MT's expected energy cost, and load sharing is more cost-efficient when the size of the data package is large and the average number of helping MTs is small.

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arXiv2015

Spatial Throughput Maximization of Wireless Powered Communication Networks

Wireless charging is a promising way to power wireless nodes' transmissions. This paper considers new dual-function access points (APs) which are able to support the energy/information transmission to/from wireless nodes. We focus on a large-scale wireless powered communication network (WPCN), and use stochastic geometry to analyze the wireless nodes' performance tradeoff between energy harvesting and information transmission. We study two cases with battery-free and battery-deployed wireless nodes. For both cases, we consider a harvest-then-transmit protocol by partitioning each time frame into a downlink (DL) phase for energy transfer, and an uplink (UL) phase for information transfer. By jointly optimizing frame partition between the two phases and the wireless nodes' transmit power, we maximize the wireless nodes' spatial throughput subject to a successful information transmission probability constraint. For the battery-free case, we show that the wireless nodes prefer to choose small transmit power to obtain large transmission opportunity. For the battery-deployed case, we first study an ideal infinite-capacity battery scenario for wireless nodes, and show that the optimal charging design is not unique, due to the sufficient energy stored in the battery. We then extend to the practical finite-capacity battery scenario. Although the exact performance is difficult to be obtained analytically, it is shown to be upper and lower bounded by those in the infinite-capacity battery scenario and the battery-free case, respectively. Finally, we provide numerical results to corroborate our study.

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