Global Positioning System (GPS) signals, though critical to numerous civilian and industrial applications, remain susceptible to spoofing due to their unencrypted nature. While many existing defenses focus on single-antenna spoofing, multi-antenna spoofing has been theorized as a significantly more potent threat. However, practical realizations of multi-antenna spoofing have been limited by the stringent requirement of nanosecond-level synchronization.

In dynamic spectrum access (DSA), secondary transmitters (SU-TX) should only be allowed to transmit on a licensed channel belonging to incumbent users (IU) when the signal-to-interference-noise-ratio (SINR) requirements of both IUs and SUs can be satisfied at the same time. However, in many DSA systems, the location and interference level of an IU are often considered sensitive data that should not be revealed, making it very challenging to ensure the QoS of both the IU and SUs while protecting IU operation security. In this paper, we propose a novel distributed SU transmit power control algorithm to solve this challenge. Our scheme can enable SINR-guaranteed coexistence between SUs and IUs and protect IUs from harmful interference, while requiring no information directly from IUs. Environmental sensing capability (ESC)'s local measurements of IU signals also undergo a security masking process to ensure IU location cannot be derived from its outputs, providing strong privacy protection for IUs. Our scheme's convergence and stability properties are experimentally demonstrated through simulations.

In dynamic spectrum access (DSA), secondary users (SU) should only be allowed to access a licensed band belonging to incumbent users (IU) when the quality-of-service (QoS) requirements of both IUs and SUs can be satisfied at the same time. However, IU’s location and its received interference strength are considered sensitive in many DSA systems which should not be revealed, making it very challenging to optimize the network utility subjected to satisfying the operation and security requirements of SUs and IUs. In this paper, we develop a secure and distributed SU transmit power control algorithm to solve this challenge. Our algorithm achieves optimal SU power control to maximize the sum of SU rates. The SINR-guaranteed coexistence between SUs and IUs are enabled to maintain effective communication, while no information is directly required from IUs. Local measurements of IU signals provided by Environmental sensing capability (ESC) also undergo a security masking process to ensure that IU location cannot be derived from its outputs. Convergence and stability properties of our algorithm and its privacy-protection strength are both theoretically analyzed and experimentally evaluated through simulations.

In resource-constrained Internet-of-Things networks, the use of conventional message authentication codes (MACs) to provide message authentication and integrity is not possible due to the large size of the MAC output. A straightforward yet naive solution to this problem is to employ a truncated MAC which undesirably sacrifices cryptographic strength in exchange for reduced communication overhead. In this article, we address this problem by proposing a novel approach for message authentication called cumulative MAC (CuMAC), which consists of two distinctive procedures: 1) aggregation and 2) accumulation. In aggregation, a sender generates compact authentication tags from segments of multiple MACs by using a systematic encoding procedure. In accumulation, a receiver accumulates the cryptographic strength of the underlying MAC by collecting and verifying the authentication tags. Embodied with these two procedures, CuMAC enables the receiver to achieve an advantageous tradeoff between the cryptographic strength and the latency in the processing of the authentication tags. Furthermore, for some latency-sensitive messages where this tradeoff may be unacceptable, we propose a variant of CuMAC that we refer to as CuMAC with speculation (CuMAC/S). In addition to the aggregation and accumulation procedures, CuMAC/S enables the sender and receiver to employ a speculation procedure for predicting future message values and precomputing the corresponding MAC segments. For the messages which can be reliably speculated, CuMAC/S significantly reduces the MAC verification latency without compromising the cryptographic strength. We have carried out a comprehensive evaluation of CuMAC and CuMAC/S through simulation and a prototype implementation on a real car.

This paper proposes a self-sustaining broadband long-range maritime communication as an alternative to the expensive and slow satellite communications in offshore areas. The proposed system, named Marinet, consists of many buoys. Each of the buoys has two units: an energy harvesting unit and a wireless communication unit. The energy harvesting unit generates electrical energy from ocean waves to support the operation of the wireless communication unit. The wireless communication unit on each buoy operates in a TV white space frequency band and connects to each other and wired high-speed gateways on land or islands to form a mesh network. The resulting mesh network provides wireless access services to marine users in their range. A prototype of the energy harvesting unit and the wireless communication unit are built and tested in the field. In addition, to ensure Marinet will maintain stable communications in rough sea states, an ocean-link-state prediction algorithm is designed. The algorithm predicts ocean link-states based on ocean wave movements. A realistic ocean simulator is designed and used to evaluate how such a link-state prediction algorithm can improve routing algorithm performance.

Link stability is an essential factor that should be considered in the design procedure of Wireless Sensor Networks (WSN) since it plays an important role in choosing different design options. Link stability becomes even more important in the case of an ocean-surface WSN, where the links between the sensors may change constantly due to ocean wave movements. Despite the importance of ocean-surface WSNs and their advantages over the existing ocean monitoring methods, current research lacks a model that describes the stability of wireless links among the buoyant sensor nodes. The existing models mostly focus on static scenarios, where both transmitter and receiver are mounted on relatively static objects such as large boats, rigs, etc. However, in most cases of ocean-surface WSNs, sensors are often installed on floating objects to take advantage of energy-harvesting systems. To fill that void, in this paper we investigate ocean waves' effects on the Line-of-Sight (LoS) link between buoyant sensors in a homogeneous WSN. Specifically, we derive the blockage probability of LoS links between a buoyant transmitter and receiver pair due to the wave movements, and analyze how environmental effects such as wind speed affect it. The ensuing results from our simulations and theoretical analyses reveal very important and unexpected facts, which are crucial and must be considered in network design.

On-demand deployment of small cells plays a key role in augmenting macro-cell coverage for outdoor hotspots, where user devices are brought together and intensively upload self-generated data. In this paper, we study spectrum sharing among rapidly deployable small cells in the uplink, even without a priori global knowledge. We propose a hybrid multi-agent approach, which allows a leading macro-cell base station (MBS) and multiple following small base stations (SBSs) to take part in a user-centric, online joint optimization of small cell deployment and uplink resource allocation. Specifically, we propose a centralized mechanism for the MBS to solve the first subproblem of small cell deployment stage by stage, based on an adversarial bandit model. Furthermore, we propose a distributed mechanism for the group of SBSs to collectively solve the second subproblem of uplink resource allocation stage by stage, based on a stochastic game model. We prove that our approach is guaranteed to produce a joint strategy, which is built upon a mixed strategy with bounded regret on the first tier and an equilibrium solution on the second tier. Our approach is validated by simulations on the aspects of convergence behavior, strategy correctness, power consumption, and spectral efficiency.

Despite the advantages that ocean surface Wireless Sensor Networks (WSN) have over traditional ocean monitoring methods, ocean surface WSN research suffers from the lack of an accurate model that describes the stability of wireless links among sensor nodes. In this paper, we investigate ocean surface waves' effects on the Line-of-Sight (LoS) link between static sensors in a WSN. Specifically, we derive the blockage probability of LoS links between a transmitter and receiver pair due to wave movements, and analyze how environmental effects like wind speed affect it. Simulation results along with oceanographic measurements validate our analyses, making our model applicable to the design and planning of WSN in the ocean environment.

Database driven dynamic spectrum sharing is one of the most promising dynamic spectrum access (DSA) solution to address the spectrum scarcity issue. In such a database-driven DSA system, the centralized spectrum management infrastructure, called spectrum access system (SAS), collects sensitive operational data of both incumbent users (IUs) and secondary users (SUs), which makes privacy protection critical in this paradigm. However, the few existing solutions rely on online trusted third party, which requires extra infrastructure and brings the risk of single point failure. To address the shortcomings of existing solutions, we propose a privacy enhanced and database-driven dynamic spectrum sharing (PeDSS) framework in this paper, which preserves the privacy for both IUs and SUs in database-driven DSA systems without the need for online trusted third party. Privacy for both IUs and SUs are formally defined and analyzed, and experiment results show that SAS under PeDSS is able to handle a single spectrum request in 0.51 ms on average, which is three orders of magnitude faster than prior arts.

Despite the advantages that ocean surface Wireless Sensor Networks (WSN) have over traditional ocean monitoring methods, ocean WSN research suffers from lack of an accurate model that describes the stability of wireless links among sensor nodes. In this paper, we are going to investigate ocean surface waves' effects on the Line-of-Sight (LoS) link between sensors in a homogeneous WSN. Specifically, we will derive the blockage probability of LoS links between a transmitter and receiver pair due to wave movements, and analyze how environmental effects like wind speed affect it. Simulation results along with oceanographic measurements validate our analyses, making our model applicable in design and planning of WSN in the ocean environment.

Dynamic spectrum access (DSA) technique has emerged as a fundamental approach to mitigate the spectrum scarcity problem. As a key form of DSA, the government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how the federal privacy is managed. In current DSA proposals, the sensitive exclusion zone (E-Zone) information of federal incumbent users (IUs) needs to be shared with a spectrum access system (SAS) to realize spectrum allocation. However, SAS is not necessarily trust-worthy for holding the sensitive IU E-Zone data, especially considering that FCC allows some industry third parties (e.g., Google) to operate SAS for better efficiency and scalability. Therefore, the current proposals dissatisfy the IUs' privacy requirement. To address the privacy issue, this paper presents an IU-privacy-preserving SAS (IP-SAS) design, which realizes the spectrum allocation process through secure computation over ciphertext based on homomorphic encryption so that none of the IU EZone information is exposed to SAS. This paper also proposes mechanisms to prevent malicious parties from compromising IP-SAS. We prove the privacy-preserving properties of IP-SAS and demonstrate the scalability and practicality of IP-SAS using experiments based on real-world data. Evaluation results show that IP-SAS can respond an SU's spectrum request in 1.25 seconds with communication overhead of 17.8 KB.

Dynamic spectrum sharing techniques applied in the UHF TV band have been developed to allow secondary WiFi transmission in areas with active TV users. This technique of dynamically controlling the exclusion zone enables vastly increasing secondary spectrum re-use, compared to the "TV white space" model where TV transmitters determine the exclusion zone and only "idle" channels can be re-purposed. However, in current such dynamic spectrum sharing systems, the sensitive operation parameters of both primary TV users (PUs) and secondary users (SUs) need to be shared with the spectrum database controller (SDC) for the purpose of realizing efficient spectrum allocation. Since such SDC server is not necessarily operated by a trusted third party, those current systems might cause essential threatens to the privacy requirement from both PUs and SUs. To address this privacy issue, this paper proposes a privacy-preserving spectrum sharing system between PUs and SUs, which realizes the spectrum allocation decision process using efficient multi-party computation (MPC) technique. In this design, the SDC only performs secure computation over encrypted input from PUs and SUs such that none of the PU or SU operation parameters will be revealed to SDC. The evaluation of its performance illustrates that our proposed system based on efficient MPC techniques can perform dynamic spectrum allocation process between PUs and SUs efficiently while preserving users' privacy.

Centralized spectrum management is one of the key dynamic spectrum access (DSA) mechanisms proposed to govern the spectrum sharing between government incumbent users (IUs) and commercial secondary users (SUs). In the current centralized DSA designs, the operation data of both government IUs and commercial SUs need to be shared with a central server. However, the operation data of government IUs are often classified information and the SU operation data may also be commercial secrets. The current system design dissatisfies the privacy requirement of both IUs and SUs, since the central server is not necessarily trustworthy for holding such sensitive operation data. To address the privacy issue, this paper presents a privacy-preserving centralized DSA system (P2-SAS), which realizes the complex spectrum allocation process of DSA through efficient secure multi-party computation. In P2-SAS, none of the IU or SU operation data would be exposed to any snooping party, including the central server itself. We formally prove the correctness and privacy-preserving property of P2-SAS and evaluate its scalability and practicality using experiments based on real-world data. Experiment results show that P2-SAS can respond an SU's spectrum request in 6.96 s with communication overhead of less than 4 MB.

Dynamic spectrum access (DSA) technique has emerged as a fundamental approach in improving spectrum utilization to mitigate the spectrum scarcity problem. As a key form of DSA, government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how federal privacy issues are managed. In current DSA proposals, the sensitive operation information of federal incumbent users (IUs) needs to be shared with a dynamic spectrum access system (SAS) to realize spectrum allocation. However, SAS is not necessarily trust-worthy for holding such sensitive IU data, especially considering that FCC allows some industry third parties (e.g., Google) to operate SAS for better efficiency and scalability. Therefore, the current proposals dissatisfy the IUs' privacy requirement. To address the privacy issues, this paper presents an IU-privacy-preserving SAS (IP-SAS) design, which realizes the spectrum allocation process through secure computation over ciphertext based on homomorphic encryption so that none of the IU operation information is exposed to SAS.

The legacy concept of exclusion zones (EZs) is inept at enabling efficient utilization of fallow spectrum by secondary users (SUs), since legacy EZs are static and overly-conservative. The notion of a static EZ implies that it has to protect incumbent users (IUs) from the union of likely interference scenarios, leading to a worst-case, conservative solution. In this paper, we propose the concept of dynamic, multi-tier EZs, which takes advantage of participatory spectrum sensing carried out by SUs to support efficient database-driven spectrum sharing while protecting IUs against SU-induced aggregate interference. Specifically, the database directly incentivizes SUs to participate in spectrum sensing, which augments geolocation database by defining smaller EZs with dynamic boundaries and creating additional spectrum access opportunities for SUs. We propose an incentive mechanism based on a two-level game-theoretic model, in which the database conducts dynamic pricing in a first-level Stackelberg game in the presence of SUs who strategically contribute to spectrum sensing in a second-level stochastic game. The existence of an equilibrium solution is proven. According to our findings, the proposed incentive mechanism for the concept of dynamic, multi-tier EZs is effective to improve spectrum utilization efficiency while guaranteeing incumbent protection.

Dynamic spectrum access (DSA) technique has emerged as a fundamental approach to mitigate the spectrum scarcity problem. As a key form of DSA, government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how the federal privacy is managed. In current DSA proposals, the sensitive exclusion zone (E-Zone) information of federal incumbent users (IUs) needs to be shared with a spectrum access system (SAS) to realize spectrum allocation. However, SAS is not necessarily trust-worthy for holding the sensitive IU E-Zone data, especially considering that FCC allows some industry third parties (e.g., Google) to operate SAS for better efficiency and scalability. Therefore, the current proposals dissatisfy the IUs' privacy requirement. To address the privacy issue, this paper presents an IU-privacy-preserving SAS (IP-SAS) design, which realizes the spectrum allocation process through secure computation over ciphertext based on homomorphic encryption.

Centralized spectrum management is one of the key dynamic spectrum access (DSA) mechanisms proposed to govern the spectrum sharing between government incumbent users (IUs) and commercial secondary users (SUs). In the current centralized DSA designs, the operation data of both government IUs and commercial SUs needs to be shared with a central server. However, the operation data of government IUs is often classified information and the SU operation data may also be commercial secret. The current system design dissatisfies the privacy requirement of both IUs and SUs since the central server is not necessarily trust-worthy for holding such sensitive operation data. To address the privacy issue, this paper presents a privacy-preserving centralized DSA system (P2-SAS), which realizes the complex spectrum allocation process of DSA through efficient secure multi-party computation. In P2-SAS, none of the IU or SU operation data would be exposed to any snooping party, including the central server itself. We formally prove the correctness and privacy-preserving property of P2-SAS and evaluate its scalability and practicality using experiments based on real-world data. Experiment results show that P2-SAS can respond an SU's spectrum request in 6.96 seconds with communication overhead of less than 4 MB.

Group signatures (GSs) is an elegant approach for providing privacy-preserving authentication. Unfortunately, modern GS schemes have limited practical value for use in large networks due to the high computational complexity of their revocation check procedures. We propose a novel GS scheme called the Group Signatures with Probabilistic Revocation (GSPR), which significantly improves scalability with regard to revocation. GSPR employs the novel notion of probabilistic revocation, which enables the verifier to check the revocation status of the private key of a given signature very efficiently. However, GSPR's revocation check procedure produces probabilistic results, which may include false positive results but no false negative results. GSPR includes a procedure that can be used to iteratively decrease the probability of false positives. GSPR makes an advantageous tradeoff between computational complexity and communication overhead, resulting in a GS scheme that offers a number of practical advantages over the prior art. We provide a proof of security for GSPR in the random oracle model using the decisional linear assumption and the bilinear strong Diffie-Hellman assumption.

Cognitive Radio (CR) is an intelligent radio technology to boost spectrum utilization and is likely to be widely spread in the near future. However, its flexible software-oriented design may be exploited by an adversary to control CR devices to launch large scale attacks on a wide range of critical wireless infrastructures. To proactively mitigate the potentially serious threat, this paper presents MadeCR, a Correlation-based Malware detection system for CR. MadeCR exploits correlations among CR applications' component actions to detect malicious behaviors. In addition, a significant contribution of the paper is a general experimentation method referred to as mutation testing to comprehensively evaluate the effectiveness of the anomaly detection method against a large number of artificial malware cases. Evaluation shows that MadeCR detects malicious behaviors within 1.10s at an accuracy of 94.9%.

Dynamic spectrum access (DSA) technique has been widely accepted as a crucial solution to mitigate the potential spectrum scarcity problem. As a key form of DSA, government is proposing to release more federal spectrum for sharing with commercial wireless users. However, the flourish of federal-commercial sharing hinges upon how privacy issues are managed. In current DSA proposals, the sensitive operation parameters of both federal incumbent users (IUs) and commercial secondary users (SUs) need to be shared with the dynamic spectrum access system (SAS) to realize efficient spectrum allocation. Since SAS is not necessarily operated by a trusted third party, the current proposals dissatisfy the privacy requirement of both IUs and SUs. To address the privacy issues, this paper presents a privacy-preserving SAS design, which realizes the complex spectrum allocation decision process of DSA through secure computation over ciphertext based on homomorphic encryption, thus none of the IU or SU operation parameters are exposed to SAS.

No abstract available.

To meet the needs of innovative sensor network applications, sensor nodes have long evolved from underpowered single microcontroller designs into complex architectures that accommodate multiple processors and Field Programmable Gate Arrays (FPGAs). We address the problem of conceiving and implementing programs for such sensor node architectures. We rely on a universal, layered hardware/software interface that provides seamless interconnection between tasks running on a micro-controller and tasks running on a FPGA. Resource sharing is handled transparently through a shared-bus communication architecture. We demonstrate our methodology, through a heterogeneous sensor node simulator called SUNSHINE [1] for an application running the sensor nodes. We validate SUNSHINE by demonstrating the applications on a multiprocessor sensor node's testbed, which consists of a FPGA, a microcontroller and a radio front-end.

The coexistence of cognitive radio (CR) networks in the same swath of spectrum has become an increasingly important problem, which is especially challenging when coexisting networks are heterogeneous (i.e., use different air interface standards), such as the case in TV white spaces. In this paper, we propose a credit-token-based spectrum etiquette framework that enables spectrum sharing among distributed heterogeneous CR networks with equal priority. Specifically, we propose a game-auction coexistence framework. Each network acts as either an offerer or a requester, and coexists with other networks via a non-cooperative game and a truthful multi-winner auction. The framework addresses the trade-offs among social welfare and offerer's revenue in the auction and requester's utility in the game. We prove that the framework guarantees system stability. Our simulation results show that the proposed coexistence framework always converges to a near-optimal distributed solution and improves coexistence fairness and spectrum utilization.

In database-driven opportunistic spectrum access, location information of secondary users plays an important role. In a database query-and-update procedure, a secondary user reports to the geolocation database of its location information, so that the updated knowledgebase facilitates location-aided incumbent protection and network coexistence. However, such database-driven spectrum sharing becomes very challenging when the secondary users are mobile. In this paper, we propose a probabilistic coexistence framework that supports mobile users by incorporating the solutions to solve two core problems: (i) white space allocation (WSA) at the database and (ii) location update control (LUC) at the users. We frame the two problems such that they interact through dynamic control of the users' location uncertainty levels. For WSA, we derive a centralized real-time solution to mitigate mutual interference among secondary users and protect primary users against harmful interference. For LUC, we design a local two-level strategy to enable both movement-driven and interference-driven control of location uncertainty. This strategy makes an appropriate trade-off between the effectiveness of interference mitigation and the cost of database queries. To evaluate our algorithms, we have carried out both theoretical model-driven and real-world trace-driven simulation experiments. Our simulation results show that the proposed framework can determine and adapt the database query intervals of mobile users to achieve near-optimal interference mitigation with minimal location updates.

Currently, the main components of most sensor nodes are a microcontroller and a radio. Their real-time and peak performance would be a bottleneck when executing computation-intensive tasks. Also, energy consumption may be high due to the long task-execution time. Several works [2]-[6] demonstrate that adding a coprocessor would be a solution to the problems. So far, no work have been done to analyze the performance of a multiprocessor sensor nodes with a FPGA coprocessor. In this paper, a design flow for heterogeneous multiprocessor sensor nodes is provided. Then, the performance comparison between multiprocessor and single processor sensor node's time and energy consumption is provided by executing applications on our in-house designed multiprocessor sensor node on a real testbed. The testbed results show that multiprocessor sensor node can either increase sensor node's execution speed or reduce the sensor node's energy consumption when the sensor node executes computation-intensive tasks.

The depletion of usable radio frequency spectrum has stimulated increasing interest in dynamic spectrum access technologies, such as cognitive radio (CR). In a scenario where multiple co-located CR networks operate in the same swath of white-space (or unlicensed) spectrum with little or no direct coordination, co-channel self-coexistence is a challenging problem. In this paper, we focus on the problem of spectrum sharing among coexisting CR networks that employ orthogonal frequency division multiple access (OFDMA) in their uplink and do not rely on inter-network coordination. An uplink soft frequency reuse (USFR) technique is proposed to enable globally power-efficient and locally fair spectrum sharing. We frame the self-coexistence problem as a non-cooperative game. In each network cell, uplink resource allocation (URA) problem is decoupled into two subproblems: subchannel allocation (SCA) and transmit power control (TPC). We provide a unique optimal solution to the TPC subproblem, while presenting a low-complexity heuristic for the SCA subproblem. After integrating the SCA and TPC games as the URA game, we design a heuristic algorithm that achieves the Nash equilibrium in a distributed manner. In both multi-operator and single-operator coexistence scenarios, our simulation results show that USFR significantly improves self-coexistence in spectrum utilization, power consumption, and intra-cell fairness.

Location spoofing attacks pose serious threats to the location based wireless network mechanisms. Most existing literature focuses on detecting location spoofing attacks or design of robust localization algorithms. However, our study shows that, in many circumstances, perfect location spoofing (PLS) can stay undetected even if robust localization algorithms or detection mechanisms are used. In this paper, we present theoretical analysis on the feasibility of beamforming-based PLS attacks and how it is affected by the anchor deployment. We formulate PLS as a nonlinear feasibility problem based on smart antenna array pattern synthesis. Due to the intractable nature of this feasibility problem, we solve it using semidefinite relaxation (SDR) in conjunction with a heuristic local search algorithm. Simulation results show the effectiveness of our analytical approach and provide insightful advices for defence against PLS attacks.

Information propagation speed (IPS) in a multihop cognitive radio network (CRN) is an important factor that affects the network's delay performance and needs to be considered in network planning and routing protocol design. The impact of primary user (PU) activities on IPS makes the problem of analyzing IPS in multihop CRNs very challenging and, hence, unsolved in existing literature. In this paper, we fill this technical void. We establish models of IPS in multihop CRNs and compute how to maximize IPS in two cases. The first case, named the maximum network IPS, maximizes IPS across a network topology over an infinite plane. The second case, named the maximum flow IPS, maximizes the IPS between a given pair of source and destination nodes separated by a fixed distance. We reveal that both maximum IPSs are determined by the PU activity level and the placement of secondary user (SU) relay nodes. We design optimal relay placement strategies in CRNs to maximize these two IPSs under different PU activity levels. The correctness of our analytical results is validated by simulations and numerical experiments.

Recent advances in cognitive radio (CR) technology have brought about a number of wireless standards that support opportunistic access to available white-space spectrum. Addressing the self-coexistence of CR networks in such an environment is very challenging, especially when coexisting networks operate in the same swath of spectrum with little or no direct coordination. In this paper, we study the problem of co-channel self-coexistence of uncoordinated CR networks that employ orthogonal frequency division multiple access (OFDMA) in the uplink. We frame the self-coexistence problem as a non-cooperative game, and propose an uplink soft frequency reuse (USFR) technique to enable globally power-efficient and locally fair sharing of white-space spectrum. In each network, uplink resource allocation is decoupled into two subproblems: subchannel allocation (SCA) and transmit power control (TPC). We provide a unique optimal solution to the TPC subproblem, and present a low-complexity heuristic for the SCA subproblem. Furthermore, we frame the TPC and SCA games, and integrate them as a heuristic algorithm that achieves the Nash equilibrium in a fully distributed manner. Our simulation results show that the proposed USFR technique significantly improves self-coexistence in several aspects, including spectrum utilization, power consumption, and intra-cell fairness.

This paper addresses the problem of anti-eavesdropping in wireless network physical layer. The main contribution of this paper is twofold. First, we propose a novel concept of artificial fading that is produced by double-beam switching of smart antenna array to intentionally corrupt unwanted wireless communication links. Second, we develop a physical layer anti-eavesdropping scheme to minimize the unnecessary coverage area, and hence, lower the chance of being eavesdropped. Our anti-eavesdropping scheme employs smart antenna with two synthesized radiation patterns, which are optimized to provide good signal quality to the intended receiver, while their overlap apart from the intended direction is minimized. During the transmission, the transmitter periodically alternates between the two optimized patterns at a high frequency, which produces severe fading to the received signal in undesired directions. Since such signals are corrupted and cannot be decoded, eavesdropping is prevented. Simulation experiments show that our anti-eavesdropping scheme outperforms single pattern beamforming in reducing the unnecessary coverage area exposed to eavesdroppers.

Energy consumption and real-time performance are two important metrics for wireless sensor networks (WSNs). To estimate these metrics, a number of simulation environments have been developed. However, these environments were made specifically for sensor nodes with fixed architectures. The recent generation of sensor nodes often has flexible architectures through the use of programmable hardware components, i.e., Field-programmable gate arrays (FPGAs). So far, no simulators have been developed to evaluate the performance of such flexible nodes in wireless networks. In this paper, we present PowerSUNSHINE, a power- and energy-estimation tool that fills the void. PowerSUNSHINE is the first scalable power/energy estimation tool for WSNs that provides an accurate prediction for both fixed and flexible sensor nodes. In this paper, we first describe requirements and challenges of building PowerSUNSHINE. Then, we present power/energy models for both fixed and flexible sensor nodes. Two testbeds, a MicaZ platform and a flexible node consisting of a microcontroller, a radio and a FPGA based co-processor, are provided to demonstrate the simulation fidelity of PowerSUNSHINE. We also discuss several evaluation results based on simulation and testbeds to show that PowerSUNSHINE is a scalable simulation tool that provides accurate estimation of power/energy consumption for both fixed and flexible sensor nodes.

In cognitive radio (CR) networks, spectrum resource that can be shared by secondary users (SUs) is always restricted by primary users (PUs). Although channel aggregation (CA) enables each SU to access multiple channels at a time, whether it is beneficial is subject to the PU activity and radio capability. In this paper, we study the feasibility and efficiency of CA in consideration of various such practical constraints and costs. First, we propose a novel channel usage model to analyze the impact of both PU and SU behaviors on the availability of white spaces. This model is very general and can capture a wide range of user behaviors. Next, we model the costs in time for performing CA. User demands in both frequency and time domains are considered to evaluate the costs for making negotiation and renewing transmission. Further, an optimal CA strategy is defined to minimize the cumulative delay for transmitting a certain amount of data. Numerical and simulation results based on real data of PU activity show that user demands on both bandwidth and duration should be carefully chosen to achieve the optimal delay performance in practice.

Information propagation speed (IPS) in a multihop cognitive radio network (CRN) is an important factor that affects the network's delay performance and needs to be considered in network planning. The impact of primary user (PU) activities on IPS makes the problem of analyzing IPS in multihop CRNs very challenging and hence unsolved in existing literature. In this paper, we fill this technical void. We establish a IPS model in multihop CRNs, and compute the maximum network IPS that maximizes IPS across a network topology over an infinite plane. We reveal that the maximum network IPS is determined by the PU activity level and the placement of secondary user relay nodes. We design optimal relay placement strategies in CRNs to maximize the network IPS under different PU activity levels. The correctness of our analytical results is validated by simulations and numerical experiments.

This paper studies the problem of location privacy protection in wireless LAN (WLAN) environment, where received signal strength (RSS) at access points (AP) can potentially be obtained by adversaries to obtain the location of a legitimate mobile station. We propose a two-step location privacy protection scheme using a linear smart antenna array on the mobile station. In the first step, the mobile station observes the arrangement of surrounding APs by moving around and estimating the path losses from itself to the APs. Based on the path loss information, in the second step, the mobile station optimizes the radiation pattern of its smart antenna so that its location privacy is protected while its communication quality is not affected. Two strategies are used in the radiation pattern optimization. The first strategy is to limit the number of APs in range of the mobile station to a safe level so that there are not enough measurements from the APs to make an estimation of the mobile station's location. If the first strategy is not possible, the mobile station falls to the second strategy, where its radiation pattern introduces maximum bias to any location estimation attempt so that the mobile station's true location is not revealed. Simulation results show that compared with traditional transmit power control (TPC) scheme, the first strategy significantly increases the probability of inadequate measurements for location computation. Simulation also demonstrates that the second strategy can significantly degenerate the precision of the positioning system. In many cases, the degenerated location precision is as low as the coverage range of the AP that the mobile station is associated with for communications. This essentially means that the second strategy can invalidate the use of RSS measurement for precise localization.

In this paper, we study deliverability of greedy routing in wireless sensor networks, where nodes are distributed over a disk area according to a homogeneous Poisson point process. In our work, we model the level of deliverability of a sensor network as the probability that all sensor nodes can successfully send their data to a base station, which is named probability of guaranteed delivery. We study the relationship between the critical transmission power of sensor nodes and the probability of guaranteed delivery, such that when all sensor nodes transmit with a higher power than the critical transmission power, the sensor network can reach the desired probability of guaranteed delivery. We identify two very tight analytical upper bounds on the critical transmission power for the idealistic u-disk model and the realistic log-normal shadowing model respectively. The correctness and tightness of these two upper bounds are verified by extensive simulations.

Most current sensor nodes are composed of a microcontroller and a radio. Their real-time and peak performance would be a bottleneck when executing compute-intensive tasks. Several works demonstrate that adding a hardware co-processor could accelerate the execution speed of the sensor nodes. So far, no simulators can simulate these new sensor nodes in wireless networks. An extension to SUNSHINE [1], a hardware-software emulator is developed to fill the void.

Simulators are important tools for analyzing and evaluating different design options for wireless sensor networks (sensornets) and hence, have been intensively studied in the past decades. However, existing simulators only support evaluations of protocols and software aspects of sensornet design. They cannot accurately capture the significant impacts of various hardware designs on sensornet performance. As a result, the performance/energy benefits of customized hardware designs are difficult to be evaluated in sensornet research. To fill in this technical void, in this paper, we describe the design and implementation of SUNSHINE (Sensor Unified aNalyzer for Software and Hardware in Networked Environments), a scalable hardware-software emulator for sensornet applications. SUNSHINE is the first sensornet simulator that effectively supports joint evaluation and design of sensor hardware and software performance in a networked context. SUNSHINE captures the performance of network protocols, software and hardware up to cycle-level accuracy through its seamless integration of three existing sensornet simulators: a network simulator TOSSIM, an instruction-set simulator SimulAVR and a hardware simulator GEZEL. SUNSHINE solves several sensornet simulation challenges, including data exchanges and time synchronizations across different simulation domains and simulation accuracy levels. SUNSHINE also provides hardware specification scheme for simulating flexible and customized hardware designs. Several experiments are given to illustrate SUNSHINE's simulation capability. Evaluation results are provided to demonstrate that SUNSHINE is an efficient tool for software-hardware co-design in sensornet research.

Most current sensor nodes are composed of a microcontroller and a radio. Their real-time and peak performance would be a bottleneck when executing compute-intensive tasks. Several works demonstrate that adding a hardware co-processor could accelerate the execution speed of the sensor nodes. So far, no simulators can simulate these new sensor nodes in wireless networks. An extension to SUNSHINE [1], a hardware-software emulator is developed to fill the void.

Broadcast routing is a critical component in the routing design. While there are plenty of routing metrics and broadcast routing schemes in current literature, it remains an unsolved problem as to which metrics are compatible with a specific broadcast routing scheme. In particular, in the wireless broadcast routing context where transmission has an inherent broadcast property, there is a potential danger of incompatible combination of broadcast routing algorithms and metrics. This paper shows that different broadcast routing algorithms have different requirements on the properties of broadcast routing metrics. The metric properties for broadcast routing algorithms in both undirected network topologies and directed network topologies are developed and proved. They are successfully used to verify the compatibility between broadcast routing metrics and broadcast routing algorithms.

The information propagation speed (IPS) of a network specifies how fast the information can be transmitted in a network. In this paper, we derive an IPS upper bound in cognitive radio networks. The upper bound is tight when the number of primary user (PU) channels is large. We discover that the IPS upper bound is determined by both the PU activity level and the transmission range of cognitive radios. When the PU activity level is below a certain threshold value, the IPS upper bound is achieved if cognitive radios transmit at their maximum transmission ranges. When the PU activity level is above the threshold, the cognitive radios have to use a smaller transmission range to reach the IPS upper bound. In addition, we also provide a numerical method for computing the threshold value of PU activity level and the optimal transmission range for achieving the IPS upper bound. The correctness of our analysis is validated by simulations. Our work can provide important insights and guidelines for optimal secondary user placement in cognitive radio networks.

The selection of routes is an important issue in wireless networks when network coding is used. Existing research formulate network-coding-aware routing as a linear optimization program. However, deploying such method in real wireless networks is impractical. To solve this issue, in this paper, a practical network-coding aware routing protocol is proposed for unicast sessions in wireless networks. The protocol is based on a novel routing metric design that captures the characteristics of network coding and unicast sessions. To ensure the novel routing metric can operate with practical and widely available path calculation mechanisms, a unique mapping process is used to map a real wireless network to a virtual network. The mapping process ensures that the paths with the biggest coding opportunities will be selected by commonly used path calculation mechanisms. Simulation results show that the proposed routing protocol is effective.

Real-time applications in ad hoc networks require fast route repair mechanisms to minimize the interruptions to their communications. Cache-based route repair schemes are popular choices since they can quickly resume communications using cached backup paths after a route break. In this paper, through thorough theoretical modeling of the cache-based route repair process, we derive the optimal cache-based route repair policy. This optimal policy considers both the overhead of the route repair schemes and the promptness of the repair action. The correctness and advantages of our optimal policy are validated by extensive simulations.

In this paper, we investigate connectivity of largescale wireless networks with a log-normal shadowing model from a percolation-based perspective, where all nodes have equal transmission capabilities and are uniformly and independently distributed at random over a large area. Firstly, based on the lognormal shadowing model, we discuss the probability that there is a link between two nodes with a distance d between them, named connection function. The connection function captures the connectivity characteristics of the wireless network in a shadow fading environment and distinguishes it from the purely random geometric graph or the purely random graph. Then, an analytical upper bound on the critical node density for asymptotic connectivity of the wireless network is derived based on the connection function. Furthermore, we also provide a more accurate estimation for the upper bound based on the previous empirical studies on purely random geometric graph, called the experiment-based upper bound. At last, the correctness and tightness of these two upper bounds are verified by extensive simulations.

Different geographic routing protocols have different requirements on routing metric designs to ensure proper operation. Combining a wrong type of routing metrics with a geographic routing protocol may produce unexpected results, such as geographic routing loops and unreachable nodes. In this paper, we propose a novel routing algebra system to investigate the compatibilities between routing metrics and three geographic routing protocols including greedy, face, and combined greedy-face routing. Five important algebraic properties, respectively, named odd symmetry, transitivity, strict order, source independence, and local minimum freeness, are defined in this algebra system. Based on these algebraic properties, the necessary and sufficient conditions for loop-free, delivery-guaranteed, and consistent routing are derived when greedy, face, and combined greedy-face routing serve as packet forwarding schemes or as path discovery algorithms, respectively. Our work provides essential criteria for evaluating and designing geographic routing protocols.

Broadcast routing is a critical component in the routing design. While there are plenty of routing metrics and broadcast routing schemes in current literature, it remains an unsolved problem as to which metrics are compatible to a specific broadcast routing scheme. In particular, in the wireless broadcast routing context where transmission has an inherent broadcast property, there is a potential danger of incompatible combination of broadcast routing algorithms and metrics. This paper shows that different broadcast routing algorithms have different requirements on the properties of broadcast routing metrics. The metric properties for typical broadcast routing algorithms in undirected topologies are developed and proved. They are successfully used to verify the compatibility between broadcast routing metrics and these algorithms. This work provides important criteria in broadcast routing metric design.

The IEEE 802.15.4 standard has no provisions for rate sensitive applications because of its ability to operate in pure CSMA/CA or TDMA modes. Some operating scenarios for rate-sensitive applications arise when one considers wireless video surveillance and target detection applications for wireless sensor networks. To support such rate-sensitive applications in wireless sensor networks, we present a multirate-based service differentiation (MRSD) based on unslotted CSMA/CA. Unlike existing priority-based service differentiation models, the MRSD defines independent virtual MACs, each of which consists of Adaptive Backoff Window Control (ABWC) and Virtual Collision Avoidance (VCA) algorithms. The ABWC dynamically adjusts the backoff window to reflect the local network state in the local collision domain. The VCA prevents virtual collisions and preempts packets with the minimal utility in the virtual collision domain. By analyzing these algorithms, we prove that the ABWC enables the achieved transmission rate to converge to the rate requirement and the VCA produces a virtual collision-free schedule to avoid degradation of the achieved transmission rate. Through the simulation, we validate our analysis and show the MRSD outperforms existing algorithms in terms of convergence to the rate requirement.

Modern frequency-agile radios are capable of dynamically changing the spectrum width and central frequency of its channels. Existing spectrum sharing algorithms often fail to exploit this characteristic to realize efficient spectrum utilization. In this paper, we present a theoretical framework that capitalize on the frequency agility of modern radios. We solve a joint spectrum sharing and end-to-end rate control problems for general wireless networks to achieve optimal spectrum efficiency with regard to network utility. Analytical and simulation results show the effectiveness of our design.

In this paper, we describe and analyze the design of a joint Transport, routing and spectrum sharing (TRSS) optimization algorithm for wireless networks with frequency- agile radios. We capitalize on the spectrum agility of modern radios which can configure both the central frequency and spectrum width of their channels. TRSS is fully distributed and is executed in two phases. In the first phase a dual driven optimizer is used to jointly adjust end-to-end transmission rate, flow-routing and spectrum width allocation. In the second phase, an innovative timing-window based spectrum access scheme is used for link layer scheduling. Analytical and simulation results show the effectiveness of our design.

Different geographic routing protocols have different requirements on routing metric designs to ensure proper operation. Combining a wrong type of routing metric with a geographic routing protocol may produce unexpected results, such as geographic routing loops and unreachable nodes. In this paper, we propose a novel routing algebra system to investigate the compatibilities between routing metrics and three geographic routing protocols including greedy, face and combined-greedy- face routing. Four important algebraic properties, respectively named odd symmetry, transitivity, source independence and local minimum freeness, are defined in this algebra system. Based on these algebraic properties, the necessary and sufficient conditions for loop-free and delivery guaranteed routing are derived when greedy, face and combined-greedy-face routing serve as packet forwarding schemes or as path discovery algorithms respectively. Our work provides essential criterions for evaluating and designing geographic routing protocols.

Recent research results show that the use of partially overlapped channel (POC) can significantly improve network capacity. In this paper we present an analytical model to estimate the capacity improvement added by the use of POC in wireless networks. We mathematically characterize the effect of node density, node distribution, network topology and traffic pattern on the performance of POC based approach. We conclude that POC based approach outperforms traditional non-overlapping multichannel approach in most scenarios except for extremely dense networks where no interference is tolerated at all. Our results indicate that POC based approaches have more advantage in relatively denser network with a heavier traffic load. These results provide us the theoretical incentive to use POCs in crowded wireless environments. We validate the results with simulations and experiments.

We have outlined a comprehensive business framework to evaluate the business impact of dynamic spectrum access technology in cognitive networks. Our model seeks to address the technical feasibility and practicality of this new technology. We attempt to obtain upper bounds on the allowable capital expenditure below which the technology might be worth pursuing for the primary providers. Cognitive radios & networks are bound to open new frontiers in the field of wireless networks and spectrum management and have the potential of becoming success stories in the near future.

The design of a routing protocol must be based on the characteristics of its target networks. The diversity of wireless networks motivates the design of different routing metrics, capturing different aspects of wireless communications. The design of routing metrics, however, is not arbitrary since it has a great impact on the proper operation of routing protocols. Combining a wrong type of routing metrics with a routing protocol may result in routing loops and suboptimal paths. We thoroughly study the relationship between routing metrics and routing protocols. Our work provides important guidelines for designing routing metrics and identifies the specific properties that a routing metric must have in order to be combined with certain type of routing protocols.

Partially overlapped channel (POC) based design, has been identified recently as a promising technique to overcome the capacity bottleneck facing wireless engineers in various networks, such as WLAN, wireless mesh network (WMN) and ad hoc networks. However, considerable confusions still exist as to the actual power of POCs to improve network capacity, especially since traditional communication system designs treat the so called adjacent channel interference (ACI) as harmful. Based on measurements of actual testbed experiments, we model the impact of POCs on system design and use numerical method to analyze network capacity improvement comparing POC-based design and traditional design. Our investigation shows that for a wide class of network settings, POC-based design allows more flexibility in wireless resource allocation, and can improve overall network capacity by as much as 100%.

This paper presents a theoretical study on distributed contention window control algorithms for achieving arbitrary bandwidth allocation policies and efficient channel utilization. By modeling different bandwidth allocation policies as an optimal contention window assignment problem, we design a general and fully distributed contention window control algorithm, called GCA (general contention window adaptation), and prove that it converges to the solution of the contention window assignment problem. By examining the stability of GCA, we identify the optimal stable point that maximizes channel utilization and provide solutions to control the stable point of GCA near the optimal point. Due to the generality of GCA, our work provides a theoretical foundation to analyze existing and design new contention window control algorithms.

An admission control algorithm must coordinate between flows to provide guarantees about how the medium is shared. In wired networks, nodes can monitor the medium to see how much bandwidth is being used. However, in ad hoc networks, communication from one node may consume the bandwidth of neighboring nodes. Therefore, the bandwidth consumption of flows and the available resources to a node are not local concepts, but related to the neighboring nodes in carrier-sensing range. Current solutions do not address how to perform admission control in such an environment so that the admitted flows in the network do not exceed network capacity. In this paper, we present a scalable and efficient admission control framework - contention-aware admission control protocol (CACP) - to support QoS in ad hoc networks. We present several options for the design of CACP and compare the performance of these options using both mathematical analysis and simulation results. We also demonstrate the effectiveness of CACP compared to existing approaches through extensive simulations.

We present MPARC (multi-priority admission and rate control), a novel joint admission control and rate policing protocol for multi-priority ad hoc networks. MPARC is based on our novel bandwidth allocation model and guarantees that the throughput of admitted realtime flows will not decrease due to later arriving realtime flows with equal or lower priorities or due to best effort flows. MPARC achieves this goal by performing accurate admission control on every newly arriving realtime flow and appropriate rate policing on all best effort traffic. Through simulation, we demonstrate that MPARC has better performance than existing approaches.

In this paper, we propose a new cross-layer framework, named QPART (QoS protocol for ad hoc realtime traffic), which provides QoS guarantees to real-time multimedia applications for wireless ad hoc networks. By adapting the contention window sizes at the MAC layer, QPART schedules packets of flows according to their unique QoS requirements. QPART implements priority-based admission control and conflict resolution to ensure that the requirements of admitted real time flows is smaller than the network capacity. The novelty of QPART is that it is robust to mobility and variances in channel capacity and imposes no control message overhead on the network.

TCP responds to all losses by invoking congestion control and avoidance algorithms, resulting in degraded end-to-end performance in lossy environments. In recent years, two approaches have been taken to improve the performance of TCP in such networks. One is local retransmission and the other is end-to-end control. These schemes either impose a heavy computational burden on base station, or cannot achieve both efficient bandwidth usage and fairness between flows because they cannot distinguish the flows on low quality wireless links from flows on high quality links. In this paper, we present a new wireless TCP protocol-End-to-end Link State Aware TCP (TCP-ELSA)-that adjusts the sending rate of a TCP flow according to the wireless link quality, but still provides good congestion control when congestion-related losses occur. The aim of TCP-ELSA is to adapt the sending rate of TCP to the link quality so that the efficiency of bandwidth usage is increased. We present simulation results that demonstrate the effectiveness of TCP-ELSA in various scenarios.