arXiv subjects

Hai Jiang

Publications and source records attributed to Hai Jiang.

At least 55 records · Page 3Linked to original sources

arXiv2017

Ambient Backscatter Networking: A Novel Paradigm to Assist Wireless Powered Communications

Ambient backscatter communication technology has been introduced recently, and is then quickly becoming a promising choice for self-sustainable communication systems as an external power supply or a dedicated carrier emitter is not required. By leveraging existing RF signal resources, ambient backscatter technology can support sustainable and independent communications and consequently open up a whole new set of applications that facilitate Internet-of-Things (IoT). In this article, we study an integration of ambient backscatter with wireless powered communication networks (WPCNs). We first present an overview of backscatter communication systems with an emphasis on the emerging ambient backscatter technology. Then we propose a novel hybrid transmitter design by combining the advantages of both ambient backscatter and wireless powered communications. Furthermore, in the cognitive radio environment, we introduce a multiple access scheme to coordinate the hybrid data transmissions. The performance evaluation shows that the hybrid transmitter outperforms traditional designs. In addition, we discuss some open issues related to the ambient backscatter networking.

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arXiv2017

Analysis of Wireless-Powered Device-to-Device Communications with Ambient Backscattering

Self-sustainable communications based on advanced energy harvesting technologies have been under rapid development, which facilitate autonomous operation and energy-efficient transmission. Recently, ambient backscattering that leverages existing RF signal resources in the air has been invented to empower data communication among low-power devices. In this paper, we introduce hybrid device-to-device (D2D) communications by integrating ambient backscattering and wireless-powered communications. The hybrid D2D communications are self-sustainable, as no dedicated external power supply is required. However, since the radio signals for energy harvesting and backscattering come from external RF sources, the performance of the hybrid D2D communications needs to be optimized efficiently. As such, we design two mode selection protocols for the hybrid D2D transmitter, allowing a more flexible adaptation to the environment. We then introduce analytical models to characterize the impacts of the considered environment factors, e.g., distribution, spatial density, and transmission load of the ambient transmitters, on the hybrid D2D communications performance. Extensive simulations show that the repulsion factor among the ambient transmitters has a non-trivial impact on the communication performance. Additionally, we reveal how different mode selection protocols affect the performance metrics.

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arXiv2017

Cyber Insurance for Heterogeneous Wireless Networks

Heterogeneous wireless networks (HWNs) composed of densely deployed base stations of different types with various radio access technologies have become a prevailing trend to accommodate ever-increasing traffic demand in enormous volume. Nowadays, users rely heavily on HWNs for ubiquitous network access that contains valuable and critical information such as financial transactions, e-health, and public safety. Cyber risks, representing one of the most significant threats to network security and reliability, are increasing in severity. To address this problem, this article introduces the concept of cyber insurance to transfer the cyber risk (i.e., service outage, as a consequence of cyber risks in HWNs) to a third party insurer. Firstly, a review of the enabling technologies for HWNs and their vulnerabilities to cyber risks is presented. Then, the fundamentals of cyber insurance are introduced, and subsequently, a cyber insurance framework for HWNs is presented. Finally, open issues are discussed and the challenges are highlighted for integrating cyber insurance as a service of next generation HWNs.

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arXiv2016

Dynamic Spectrum Leasing with Two Sellers

This paper studies dynamic spectrum leasing in a cognitive radio network. There are two spectrum sellers, who are two primary networks, each with an amount of licensed spectrum bandwidth. When a seller has some unused spectrum, it would like to lease the unused spectrum to secondary users. A coordinator helps to perform the spectrum leasing stage-by-stage. As the two sellers may have different leasing period, there are three epochs, in which seller 1 has spectrum to lease in Epochs II and III, while seller 2 has spectrum to lease in Epochs I and II. Each seller needs to decide how much spectrum it should lease to secondary users in each stage of its leasing period, with a target at revenue maximization. It is shown that, when the two sellers both have spectrum to lease (i.e., in Epoch II), the spectrum leasing can be formulated as a non-cooperative game. Nash equilibria of the game are found in closed form. Solutions of the two users in the three epochs are derived.

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arXiv2015

Opportunistic Cooperative Channel Access in Distributed Wireless Networks with Decode-and-Forward Relays

This letter studies distributed opportunistic channel access in a wireless network with decode-and-forward relays. All the sources use channel contention to get transmission opportunity. If a source wins the contention, the channel state information in the first-hop channel (from the source to its relay) is estimated, and a decision is made for the winner source to either give up the transmission opportunity and let all sources start a new contention, or transmit to the relay. Once the relay gets the traffic, it may have a sequence of probings of the second-hop channel (from the relay to the destination). After each probing, if the second-hop channel is good enough, the relay transmits to the destination and completes the transmission process of the source; otherwise, the relay decides either to give up and let all sources start a new contention, or to continue to probe the second-hop channel. The optimal decision strategies for the two hops are derived in this letter. The first-hop strategy is a pure-threshold strategy, i.e., when the first-hop channel signal-to-noise ratio (SNR) is more than a threshold, the winner source should transmit to the relay, and subsequently the second-hop strategy should let the relay keep probing the second-hop channel until a good enough second-hop channel is observed. Simulation results show that our scheme is beneficial when the second-hop channels have larger average SNR.

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arXiv2014

Performance Limits of Segmented Compressive Sampling: Correlated Samples versus Bits

This paper gives performance limits of the segmented compressive sampling (CS) which collects correlated samples. It is shown that the effect of correlation among samples for the segmented CS can be characterized by a penalty term in the corresponding bounds on the sampling rate. Moreover, this penalty term is vanishing as the signal dimension increases. It means that the performance degradation due to the fixed correlation among samples obtained by the segmented CS (as compared to the standard CS with equivalent size sampling matrix) is negligible for a high-dimensional signal. In combination with the fact that the signal reconstruction quality improves with additional samples obtained by the segmented CS (as compared to the standard CS with sampling matrix of the size given by the number of original uncorrelated samples), the fact that the additional correlated samples also provide new information about a signal is a strong argument for the segmented CS.

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arXiv2014

Permutation Enhanced Parallel Reconstruction with A Linear Compressive Sampling Device

In this letter, a permutation enhanced parallel reconstruction architecture for compressive sampling is proposed. In this architecture, a measurement matrix is constructed from a block-diagonal sensing matrix and the sparsifying basis of the target signal. In this way, the projection of the signal onto the sparsifying basis can be divided into several segments and all segments can be reconstructed in parallel. Thus, the computational complexity and the time for reconstruction can be reduced significantly. This feature is especially appealing for big data processing. Furthermore, to reduce the number of measurements needed to achieve the desired reconstruction error performance, permutation is introduced for the projection of the signal. It is shown that the permutation can be performed implicitly by using a pre-designed measurement matrix. Thus, the permutation enhanced parallel reconstruction can be achieved with a linear compressive sampling device.

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arXiv2014

Efficient Strategies for Single/Multi-Target Jamming on MIMO Gaussian Channels

The problem of jamming on multiple-input multiple-output (MIMO) Gaussian channels is investigated in this paper. In the case of a single target legitimate signal, we show that the existing result based on the simplification of the system model by neglecting the jamming channel leads to losing important insights regarding the effect of jamming power and jamming channel on the jamming strategy. We find a closed-form optimal solution for the problem under a positive semi-definite (PSD) condition without considering simplifications in the model. If the condition is not satisfied and the optimal solution may not exist in closed-form, we find the optimal solution using a numerical method and also propose a suboptimal solution in closed-form as a close approximation of the optimal solution. Then, the possibility of extending the results to solve the problem of multi-target jamming is investigated for four scenarios, i.e., multiple access channel, broadcasting channel, multiple transceiver pairs with orthogonal transmissions, and multiple transceiver pairs with interference, respectively. It is shown that the proposed numerical method can be extended to all scenarios while the proposed closed-form solutions for jamming may be applied in the scenarios of the multiple access channel and multiple transceiver pairs with orthogonal transmissions. Simulation results verify the effectiveness of the proposed solutions.

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arXiv2013

Permutation Meets Parallel Compressed Sensing: How to Relax Restricted Isometry Property for 2D Sparse Signals

Traditional compressed sensing considers sampling a 1D signal. For a multidimensional signal, if reshaped into a vector, the required size of the sensing matrix becomes dramatically large, which increases the storage and computational complexity significantly. To solve this problem, we propose to reshape the multidimensional signal into a 2D signal and sample the 2D signal using compressed sensing column by column with the same sensing matrix. It is referred to as parallel compressed sensing, and it has much lower storage and computational complexity. For a given reconstruction performance of parallel compressed sensing, if a so-called acceptable permutation is applied to the 2D signal, we show that the corresponding sensing matrix has a smaller required order of restricted isometry property condition, and thus, storage and computation requirements are further lowered. A zigzag-scan-based permutation, which is shown to be particularly useful for signals satisfying a layer model, is introduced and investigated. As an application of the parallel compressed sensing with the zigzag-scan-based permutation, a video compression scheme is presented. It is shown that the zigzag-scan-based permutation increases the peak signal-to-noise ratio of reconstructed images and video frames.

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arXiv2013

Sum-Rate Maximization with Minimum Power Consumption for MIMO DF Two-Way Relaying: Part I - Relay Optimization

The problem of power allocation is studied for a multiple-input multiple-output (MIMO) decode-and-forward (DF) two-way relaying system consisting of two source nodes and one relay. It is shown that achieving maximum sum-rate in such a system does not necessarily demand the consumption of all available power at the relay. Instead, the maximum sum-rate can be achieved through efficient power allocation with minimum power consumption. Deriving such power allocation, however, is nontrivial due to the fact that it generally leads to a nonconvex problem. In Part I of this two-part paper, a sum-rate maximizing power allocation with minimum power consumption is found for MIMO DF two-way relaying, in which the relay optimizes its own power allocation strategy given the power allocation strategies of the source nodes. An algorithm is proposed for efficiently finding the optimal power allocation of the relay based on the proposed idea of relative water-levels. The considered scenario features low complexity due to the fact that the relay optimizes its power allocation without coordinating the source nodes. As a trade-off for the low complexity, it is shown that there can be waste of power at the source nodes because of no coordination between the relay and the source nodes. Simulation results demonstrate the performance of the proposed algorithm and the effect of asymmetry on the considered system.

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arXiv2012

Sum-Rate Maximization with Minimum Power Consumption for MIMO DF Two-Way Relaying: Part II - Network Optimization

In Part II of this two-part paper, a sum-rate-maximizing power allocation with minimum power consumption is found for multiple-input multiple-output (MIMO) decode-and-forward (DF) two-way relaying (TWR) in a network optimization scenario. In this scenario, the relay and the source nodes jointly optimize their power allocation strategies to achieve network optimality. Unlike the relay optimization scenario considered in part I which features low complexity but does not achieve network optimality, the network-level optimal power allocation can be achieved in the network optimization scenario at the cost of higher complexity. The network optimization problem is considered in two cases each with several subcases. It is shown that the considered problem, which is originally nonconvex, can be transferred into different convex problems for all but two subcases. For the remaining two subcases, one for each case, it is proved that the optimal strategies for the source nodes and the relay must satisfy certain properties. Based on these properties, an algorithm is proposed for finding the optimal solution. The effect of asymmetry in the number of antennas, power limits, and channel statistics is also considered. Such asymmetry is shown to have a negative effect on both the achievable sum-rate and the power allocation efficiency in MIMO DF TWR. Simulation results demonstrate the performance of the proposed algorithm and the effect of asymmetry in the system.

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arXiv2012

Channel Exploration and Exploitation with Imperfect Spectrum Sensing in Cognitive Radio Networks

In this paper, the problem of opportunistic channel sensing and access in cognitive radio networks when the sensing is imperfect and a secondary user has limited traffic to send at a time is investigated. Primary users' statistical information is assumed to be unknown, and therefore, a secondary user needs to learn the information online during channel sensing and access process, which means learning loss, also referred to as regret, is inevitable. In this research, the case when all potential channels can be sensed simultaneously is investigated first. The channel access process is modeled as a multi-armed bandit problem with side observation. And channel access rules are derived and theoretically proved to have asymptotically finite regret. Then the case when the secondary user can sense only a limited number of channels at a time is investigated. The channel sensing and access process is modeled as a bi-level multi-armed bandit problem. It is shown that any adaptive rule has at least logarithmic regret. Then we derive channel sensing and access rules and theoretically prove they have logarithmic regret asymptotically and with finite time. The effectiveness of the derived rules is validated by computer simulation.

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arXiv2011

Relay Selection and Performance Analysis in Multiple-User Networks

This paper investigates the relay selection (RS) problem in networks with multiple users and multiple common amplify-and-forward (AF) relays. Considering the overall quality-of-service of the network, we first specify our definition of optimal RS for multiple-user relay networks. Then an optimal RS (ORS) algorithm is provided, which is a straightforward extension of an RS scheme in the literature that maximizes the minimum end-to-end receive signal-to-noise ratio (SNR) of all users. The complexity of the ORS is quadratic in both the number of users and the number of relays. Then a suboptimal RS (SRS) scheme is proposed, which has linear complexity in the number of relays and quadratic complexity in the number of users. Furthermore, diversity orders of both the ORS and the proposed SRS are theoretically derived and compared with those of a naive RS scheme and the single-user RS network. It is shown that the ORS achieves full diversity; while the diversity order of the SRS decreases with the the number of users. For two-user networks, the outage probabilities and array gains corresponding to the minimum SNR of the RS schemes are derived in closed forms. It is proved that the advantage of the SRS over the naive RS scheme increases as the number of relays in the network increases. Simulation results are provided to corroborate the analytical results.

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arXiv2011

Distributed Opportunistic Channel Access in Wireless Relay Networks

In this paper, the problem of distributed opportunistic channel access in wireless relaying is investigated. A relay network with multiple source-destination pairs and multiple relays is considered. All the source nodes contend through a random access procedure. A winner source node may give up its transmission opportunity if its link quality is poor. In this research, we apply the optimal stopping theory to analyze when a winner node should give up its transmission opportunity. By assuming the winner node has information of channel gains of links from itself to relays and from relays to its destination, the existence and uniqueness of an optimal stopping rule are rigorously proved. It is also found that the optimal stopping rule is a pure-threshold strategy. The case when the winner node does not have information of channel gains of links from relays to its destination is also studied. Two stopping problems exist, one in the main layer (for channel access of source nodes), and the other in the sub-layer (for channel access of relay nodes). An intuitive stopping rule, where the sub-layer and the main layer maximize their throughput respectively, is shown to be a semi-pure-threshold strategy. The intuitive stopping rule turns out to be non-optimal. An optimal stopping rule is then derived theoretically. Our research reveals that multi-user (including multi-source and multi-relay) diversity and time diversity can be fully utilized in a relay network by our proposed strategies.

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arXiv2009

Cooperative Precoding/Resource Allocation Games under Spectral Mask and Total Power Constraints

The use of orthogonal signaling schemes such as time-, frequency-, or code-division multiplexing (T-, F-, CDM) in multi-user systems allows for power-efficient simple receivers. It is shown in this paper that by using orthogonal signaling on frequency selective fading channels, the cooperative Nash bargaining (NB)-based precoding games for multi-user systems, which aim at maximizing the information rates of all users, are simplified to the corresponding cooperative resource allocation games. The latter provides additional practically desired simplifications to transmitter design and significantly reduces the overhead during user cooperation. The complexity of the corresponding precoding/resource allocation games, however, depends on the constraints imposed on the users. If only spectral mask constraints are present, the corresponding cooperative NB problem can be formulated as a convex optimization problem and solved efficiently in a distributed manner using dual decomposition based algorithm. However, the NB problem is non-convex if total power constraints are also imposed on the users. In this case, the complexity associate with finding the NB solution is unacceptably high. Therefore, the multi-user systems are categorized into bandwidth- and power-dominant based on a bottleneck resource, and different manners of cooperation are developed for each type of systems for the case of two-users. Such classification guarantees that the solution obtained in each case is Pareto-optimal and actually can be identical to the optimal solution, while the complexity is significantly reduced. Simulation results demonstrate the efficiency of the proposed cooperative precoding/resource allocation strategies and the reduced complexity of the proposed algorithms.

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arXiv2008

Optimal Medium Access Protocols for Cognitive Radio Networks

This paper focuses on the design of medium access control protocols for cognitive radio networks. The scenario in which a single cognitive user wishes to opportunistically exploit the availability of empty frequency bands within parts of the radio spectrum having multiple bands is first considered. In this scenario, the availability probability of each channel is unknown a priori to the cognitive user. Hence efficient medium access strategies must strike a balance between exploring (learning) the availability probability of the channels and exploiting the knowledge of the availability probability identified thus far. For this scenario, an optimal medium access strategy is derived and its underlying recursive structure is illustrated via examples. To avoid the prohibitive computational complexity of this optimal strategy, a low complexity asymptotically optimal strategy is developed. Next, the multi-cognitive user scenario is considered and low complexity medium access protocols, which strike an optimal balance between exploration and exploitation in such competitive environments, are developed.

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arXiv2008

Optimal Medium Access Control in Cognitive Radios: A Sequential Design Approach

The design of medium access control protocols for a cognitive user wishing to opportunistically exploit frequency bands within parts of the radio spectrum having multiple bands is considered. In the scenario under consideration, the availability probability of each channel is unknown a priori to the cognitive user. Hence efficient medium access strategies must strike a balance between exploring the availability of channels and exploiting the opportunities identified thus far. Using a sequential design approach, an optimal medium access strategy is derived. To avoid the prohibitive computational complexity of this optimal strategy, a low complexity asymptotically optimal strategy is also developed. The proposed strategy does not require any prior statistical knowledge about the traffic pattern on the different channels.

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arXiv2007

Cognitive Medium Access: Exploration, Exploitation and Competition

This paper establishes the equivalence between cognitive medium access and the competitive multi-armed bandit problem. First, the scenario in which a single cognitive user wishes to opportunistically exploit the availability of empty frequency bands in the spectrum with multiple bands is considered. In this scenario, the availability probability of each channel is unknown to the cognitive user a priori. Hence efficient medium access strategies must strike a balance between exploring the availability of other free channels and exploiting the opportunities identified thus far. By adopting a Bayesian approach for this classical bandit problem, the optimal medium access strategy is derived and its underlying recursive structure is illustrated via examples. To avoid the prohibitive computational complexity of the optimal strategy, a low complexity asymptotically optimal strategy is developed. The proposed strategy does not require any prior statistical knowledge about the traffic pattern on the different channels. Next, the multi-cognitive user scenario is considered and low complexity medium access protocols, which strike the optimal balance between exploration and exploitation in such competitive environments, are developed. Finally, this formalism is extended to the case in which each cognitive user is capable of sensing and using multiple channels simultaneously.

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