Miao Pan

ABSTRACT Synchronization is a challenging task in ultra wideband (UWB) communications, and becomes more difficult in UWB based wireless sensor networks (WSNs) in the presence of multi-user interference (MUI). For such a system, we develop a synchronization scheme including a novel design of transmitted reference (TR) signal model to avoid MUI and an energy-efficient synchronization algorithm. The synchronization signal of cluster-head is designed to be TR symbols with normal reference pulse and the interfering signal of common neighbour nodes is designed to be TR symbols with alternant anti-polar reference pulse, thus the MUI-free operation is obtained. Furthermore, the synchronization algorithm employs sample mean and energy detection relying on the periodicity in the mean of synchronization signal. Theoretic analysis and simulative results prove that the proposed scheme is both reliable and scalable.

ABSTRACT In this paper we propose and discuss an innovative infrastructure-assisted routing protocol for the ad hoc network overall or partial under the coverage of the infrastructure network. The basic idea of this design is to make full use of the infrastructure network's notable features to support the implementation of route discovery and maintenance for the purpose of not only highly reducing time, communication and storage complexity but also balancing traffic load of the ad hoc network. In this protocol, each node detaches link state with the neighbor nodes and reports the changes to the infrastructure network using the triggered update mechanism, while the infrastructure network stores the full knowledge of topology, computes routes on-demand with latency as the edge weight, and distributes the sub-route records to relevant relay nodes using the multi-sub- route relay mechanism. Those sub-routes are typically, but not necessarily, of the same length. Since not all nodes communicate with the infrastructure network directly, the ad hoc network are divided into a set of zones, the light zones and the dark zones, and different strategies, i.e. the link state algorithm and the source routing algorithm, are employed in different zones. We refer to the protocol as the light dark routing (LDR) protocol.

This driven by the need to promote a more efficient use of radio resources and improve the operators' profits, resource allocation has turned into a joint technical and economical problem. At the same time, as a possible enabling solution, game theory has been applied to either dynamic spectrum access (DSA) or joint radio resource management (JRRM) in wireless communication research recently. In this paper, we propose a novel DSA and JRRM combined approach to resource allocation in cooperative networks. With the scenario that distributed reconfigurable radio access networks (RAN) are controlled by different operators, the emerging concept of resource trading is introduced and new entities, such as trading agents (TA), are described. Meanwhile, Shapley value in cooperative game as well as its economic model is exploited to share the profits among the trading RANs. Numerical results show that comparing with existing DSA or JRRM methods, our scheme has better effect in maximizing the individual operator's profits and improving the efficiency of radio resources utilization.

ABSTRACT B3G wireless networks are expected to be characterized by the pouring of different radio access technologies (RAT) and diversified service requirements. In parallel with this, the irreconcilable conflicts between the great demand for radio spectrum and its scarcity bring the issues of dynamic spectrum management (DSM) and efficiency in spectrum utilization into our sight. This article aims to investigate the possibilities of a novel DSM scheme with the help of game theory in microeconomics. In the context of distributed reconfigurable networks in the charge of one operator, we propose market competition based dynamic spectrum management (MCDSM) schemes based on multi-agent models. The competition mechanism, related technologies and proposed algorithm are also described in details. The study reveals that MCDSM scheme utilizes the spectrum efficiently, enhances the fairness among different radio access networks (RAN) and maximizes the operator's profits

... In the context of distributed reconfigurable networks in the charge of different operators, bargaining based dynamic spectrum management (BDSM) scheme introduces trading agent (TA), changing bargaining ability as well as revenue-sharing mechanism to facilitate the ...

Sensor-enabled RFID technology has generated a lot of interest from industries lately. Integrated with miniaturized sensors, RFID tags could provide not only the IDs but also valuable real-time information about the state of the corresponding objects or the surrounding environment, which is beneficial to many practical applications, such as warehouse management and inventory control. In this paper, we study the problem on how to design efficient protocols to collect such sensor information from numerous tags in a large-scale RFID system with a number of readers deployed. Different from information collection in the small RFID system covered by only one reader, in the multi-reader scenario, each reader has to first find out which tags located in its interrogation region in order to read information from them. We start with two categories of warm-up solutions that are directly extended from the existing information collection protocols for single-reader RFID systems, and show that all of them do not work well for the multi-reader information collection problem due to their inefficiency of identifying the interrogated tags. Then, we propose a novel solution, called the Bloom filter based Information Collection protocol (BIC). In BIC, the interrogated tag identification can be efficiently achieved with a distributively constructed Bloom filter, which significantly reduces the communication overhead and thus the protocol execution time. Extensive simulations show that BIC performs better than all the warm-up solutions and its execution time is within 3 times of the lower bound.

The essential impediment to apply cognitive radio (CR) technology for efficient spectrum utilization lies in the uncertainty of licensed spectrum supply. In this paper, we propose a novel architecture for spectrum harvesting and sharing, and investigate the joint routing and frequency scheduling problem in multi-hop cognitive radio networks (CRNs) under uncertain spectrum supply. We introduce a new service provider, Secondary Service Provider (SSP), to facilitate the accessing for secondary users (SUs). We model the vacancy of available bands with a series of random variables, and mathematically describe the corresponding frequency scheduling and flow routing constraints. From the SSP's point of view, we characterize the CRN performance with a pair of parameters (α, β), and present an optimization problem to minimize the required network-wide spectrum resource at the (α,β) level. Given that (α, β) level is specified, we obtain a lower bound for the optimization problem and develop a threshold based coarse-grained fixing algorithm for a feasible solution. Simulation results show that (i) for any (α,β) level, the proposed algorithm provides a near-optimal solution to the formulated NP-hard problem, and (ii) the (α,β) based solution is better than the expected bandwidth based one in terms of blocking ratio and spectrum utilization in multi-hop CRNs.

Abstract Microeconomics-inspired spectrum auctions can dramatically improve the spectrum utilization for wireless networks to satisfy the ever increasing service demands. However, the back-room dealing (ie, the frauds of the insincere auctioneer and the bid-rigging between ...

Network capacity investigation has been intensive in the past few years. A large body of work has appeared in the literature. However, so far most of the effort has been made on two-dimensional wireless networks only. With the great development of wireless technologies, wireless networks are envisioned to extend from two-dimensional space to three-dimensional space. In this paper, we investigate for the first time the throughput capacity of 3D regular ad hoc networks (RANETs) and of 3D heterogeneous ad hoc networks (HANETs), respectively, by employing a generalized physical model. In 3D RANETs, we assume that the nodes are regularly placed, while in 3D HANETs, we consider that the nodes are distributed according to a general Nonhomogeneous Poisson Process (NPP). We find both lower and upper bounds in both types of networks in a broad power propagation regime, i.e., when the path loss exponent is no less than 2.

Throughput maximization is a key challenge for wireless applications in cognitive Vehicular Ad-hoc Networks (C-VANETs). As a potential solution, cooperative communications, which may increase link capacity by exploiting spatial diversity, has attracted a lot of attention in recent years. However, if link scheduling is considered, this transmission mode may perform worse than direct transmission in terms of end-to-end throughput. In this paper, we propose a cooperative communication aware link scheduling scheme and investigate the throughput maximization problem in C-VANETs. Regarding the features of cooperative communications and the availability of licensed spectrum, we extend the links into cooperative links/general links, define extended link-band pairs, and form a 3-dimensional (3-D) cooperative conflict graph to characterize the conflict relationship among those pairs. Given all cooperative independent sets in this graph, we mathematically formulate an end-to-end throughput maximization problem and near-optimally solve it by linear programming. Due to the NP-completeness of finding all independent sets, we also develop a heuristic pruning algorithm for cooperative communication aware link scheduling. Our simulation results show that the proposed scheme is effective in increasing end-to-end throughput for the session in C-VANETs.

ABSTRACT The multi-hop cellular network (MCN) is an evolved paradigm for mobile communications, which integrates the ad hoc characteristics into the conventional cellular systems. Similar to ad hoc networks, the performance of MCNs relies on the hypothesis that each node accepts to forward traffic for the benefit of others, which may not hold with the possible presence of selfish users. In order to stimulate the collaboration among mobile nodes in MCNs, in this paper, we propose a light-weighted secure incentive protocol (LIP). We introduce a novel reward model, in which not the source and/or the destination but the network operator credits the forwarding nodes. It is shown that our model is much more realistic for MCNs in practice and simplifies the payment scheme design as well. LIP exploits a reactive receipt-submission mechanism to identify node behavior, which significantly reduces the communication overhead. Security analysis shows that LIP can resist various attacks. The efficiency of LIP is validated through the performance evaluation.

The essential impediment to apply cognitive radio (CR) technology for spectrum utilization improvement lies in the uncertainty of licensed spectrum supply. In this paper, we investigate the joint routing and link scheduling problem of multi-hop CR networks under uncertain spectrum supply. We model the vacancy of licensed bands with a series of random variables, and introduce corresponding scheduling constraints and flow routing constraints for such a network. From a CR network planner/operator's point of view, we characterize the network with a pair of (α, β) parameters, and present a mathematical formulation with the goal of minimizing the required network-wide spectrum resource at the (α, β) level. Given that (α, β) is specified, we derive a lower bound for the optimization problem and develop a threshold based coarse-grained fixing algorithm for a feasible solution. Simulation results show that i) for any (α, β) level, the proposed algorithm provides a near-optimal solution to the formulated NP-hard problem; ii) the (α, β) based solution is better than expected bandwidth based one in terms of blocking ratio as well as spectrum utilization in CR networks..

Cognitive Radio technology releases the spectrum from shackles of authorized licenses and facilitates the trading of spectrum bands. In the spectrum market, primary users (PUs) set prices for their vacant bands and sell them for monetary gains, and secondary users (SUs) buy the bands and opportunistically use them to satisfy their service demands when the PUs are not active. However, when there are multiple bands available for the SUs to access, the SU confronts the challenges of how to choose bands and how to split his traffic over them considering both the contention from peer SUs as well as the unpredictable activities of the PUs. In this paper, we propose a return and risk model to represent these concerns of the SU, and help the SU to make appropriate decisions of traffic distribution over available spectrum bands, either the bands belonging to SU itself or the bands shared with PUs. The simulation and analysis show that our spectrum sharing scheme is efficient in terms of maximum return for given risk or minimum risk for given return, and is also effective in improving the spectrum utilization and SUs' satisfactory degrees.

Spectrum trading creates more accessing opportunities for secondary users (SUs) and economically benefits the primary users (PUs). However, it is challenging to implement spectrum trading in multi-hop cognitive radio networks (CRNs) due to harsh cognitive radio (CR) requirements on SUs' devices and complex conflict and competition relationship among different CR sessions. Unlike the per-user based spectrum trading designs in previous studies, in this paper, we propose a novel session based spectrum trading system, spectrum clouds, in multi-hop CRNs. In spectrum clouds, we introduce a new service provider, called secondary service provider (SSP), to harvest the available spectrum bands and facilitate the accessing of SUs without CR capability. The SSP also conducts spectrum trading among CR sessions w.r.t. their conflicts and competitions. Leveraging a 3-dimensional (3-D) conflict graph, we mathematically describe the conflicts and competitions among the candidate sessions for spectrum trading. Given the rate requirements and bidding values of candidate trading sessions, we formulate the optimal spectrum trading into the SSP's revenue maximization problem under multiple cross-layer constraints in multi-hop CRNs. In view of the NP-hardness of the problem, we have also developed heuristic algorithms to pursue feasible solutions. Through extensive simulations, we show that the solutions found by the proposed algorithms are close to the optimal one.