Wireless Algorithms, Systems, and Applications

Coverage is critical for wireless sensor networks to monitor a region of interest and to provide a good quality of service. In many application scenarios, full coverage is required, which means every point inside the region (excluding the obstacles) must be covered by at least one sensor. The problem of using the minimum number of sensors to achieve full coverage for an arbitrary region with obstacles is NP-hard. Most existing coverage methods, such as contour-based ones, simply place sensors along the boundaries to cover the holes that are near the obstacles and the region boundary. These methods are inefficient especially when the obstacles or the region are irregular. In this paper, based on computational geometry, we design a full coverage method, which accurately finds the uncovered holes and places sensors efficiently for both the regular and irregular obstacles and regions. Specifically, we show that the more irregular the obstacles and the region are, the more sensors our method can save.

Connected dominating set (CDS) is widely used in wireless networks as a virtual backbone for communication and routing between nodes. In order to measure the quality of a CDS, most researches in this area focus on reducing the size of a CDS, neglecting other important metrics, such as diameter between two communication parties. This paper considers the diameter as a quality factor for CDS construction, and develops two new heuristic algorithms. In particular, the CDS computed by the first algorithm has constant ratios 9 and 3 for its size and diameter, respectively. And that of the second algorithm has constant ratios 5 + ln 10 and 2. Both theoretical analysis and simulation show out the performance of the algorithms.

In this paper we study the

target Q-coverage

(TQC) problem where each target needs to be covered by different numbers of sensors. We try to find a collection of

Q

-

covsets

which satisfy the coverage quality requirement to maximize the network lifetime. We first prove that the problem is NP-Hard. Then we design a greedy algorithm to efficiently compute the

Q

-

covsets

. Finally, simulation results are presented to verify our approach.

Due to the large-scale ad hoc deployments and wireless interference, data aggregation is a fundamental but time consuming task in wireless sensor networks. This paper focuses on the latency of data aggregation. Previously, it has been proved that the problem of minimizing the latency of data aggregation is NP-hard [1]. Using maximum independent set and first fit algorithms, in this study we design a scheduling algorithm, Peony-tree-based Data Aggregation (PDA), which has a latency bound of 15

R

 + Δ− 15, where

R

is the network radius (measured in hops) and Δ is the maximum node degree. We theoretically analyze the performance of PDA based on different network models, and further evaluate it through extensive simulations. Both the analytical and simulation results demonstrate the advantages of PDA over the state-of-art algorithm in [2], which has a latency bound of 23

R

 + Δ− 18.

In this study, we investigate the problem of achieving proportional fairness via Access Point (AP) association in multi-rate WLANs. This problem is formulated as a non-linear program with an objective function of maximizing the total user bandwidth utilities in the whole network. It is NP-hard, and therefore effort in this paper is made to seek approximate solutions. We propose a centralized algorithm to derive the user-AP association via relaxation. Such a relaxation may cause a large integrality gap. Therefore a compensation function is introduced to guarantee that our algorithm can achieve at least half of the optimal solution in the worst-case scenario theoretically. Extensive simulation study has been reported to validate and compare the performances of our algorithms with those of the state-of-the-art.

Connected dominating set (CDS) has a wide range of applications in mutihop wireless networks. The Minimum CDS problem has been studied extensively in mutihop wireless networks with uniform communication ranges. However, in practice the nodes may have different communication ranges either because of the heterogeneity of the nodes, or due to interference mitigation, or due to a chosen range assignment for energy conservation. In this paper, we present a greedy approximation algorithm for computing a Minimum CDS in multihop wireless networks with disparate communications ranges and prove that its approximation ratio is better than the best one known in the literature. Our analysis utilizes a tighter relation between the independence number and the connected domination number.

The approach of using topology control to reduce interference in wireless sensor networks has attracted attention of many researchers. There are several definitions of interference in the literature. In a wireless sensor network, the interference at a node may be caused by an edge that is transmitting data, or it occurs because the node itself is within the transmission range of another. The interference load of an edge is the number of nodes that are in the disks defined by the end nodes of this edge with a radius which is either the Euclidean distance or the power level of the end nodes. In this paper we show that the problem of assigning power level to a set of nodes in the plane to yield a connected geometric graph whose edges have bounded interference is NP-complete under both edge interference definitions. We also study the performance of a number of heuristics through simulation.

Interference-aware scheduling for wireless communications is crucial to improve the network throughput. In this paper, we study the problem of Maximum Weighted Independent Set of Links (MWISL) under the physical interference model in wireless networks. Given a set of communication links distributed in a two-dimensional Euclidean plane, assume each link is associated with a positive weight which represents the benefit of transmitting along the link, the objective is to seek an independent set of links subject to the physical interference constraints with maximum weighted sum. To the best of our knowledge, no algorithm for MWISL under physical interference model has been proposed. We focus on MWISL in the oblivious power assignment setting.

A mobile device may run energy consuming multimedia applications, such as video streaming. Thus, power management is an important issue in mobile devices. In this paper, we propose a QoS-guaranteed energy-efficient packet scheduling algorithm for IEEE 802.16-2009 (WiMax) network interfaces. The integration of packet scheduling and sleep mode operation can make IEEE 802.16-2009-enabled mobile devices more energy efficient. Simulation results show that the proposed packet scheduling algorithm has 14.37% less energy consumption than the naïve algorithm, and it does not sacrifice average packet delay. The contributions of our proposed algorithm are that our algorithm is suitable for wireless environments where connections come and go rapidly and the time complexity of our algorithm is low.

Barrier coverage problem is one of important issues in wireless sensor networks. In this paper we study the minimum energy cost

k

-barrier coverage problem in wireless sensor network in which each sensor has

l

 + 1 sensing power levels. First, we transform the minimum energy cost

k

-barrier coverage problem into a minimum cost flow problem with side constraints. Then we use Lagrangian relaxation technique to solve this minimum cost flow problem. Moreover, we propose two efficient heuristics for the minimum energy cost

k

-barrier coverage problem. Simulations evaluate that our algorithms are efficient.

In this paper, we study the distributed cooperative power allocation problem in a single-cell cognitive radio system. We build up a dynamic power allocation model via differential game using two formulated cost functions. Moreover, we propose a distributed cooperative power allocation algorithm based on differential game (DCPADG) under the condition that the average power limits and QoS constraints of secondary users (SUs) are guaranteed. Numerical results demonstrate that the proposed DCPADG algorithm can effectively reduce the transmit power and improve the throughput of SUs.

In this paper, we investigate how to design energy-efficient localized routing in a large-scale three-dimensional (3D) wireless network. Several 3D localized routing protocols were proposed to seek either energy efficiency or delivery guarantee in 3D wireless networks. However, recent results [1, 2] showed that there is no deterministic localized routing algorithm that guarantees either delivery of packets or energy efficiency of its routes in 3D networks. In this paper, we focus on design of a simple localized routing method which can provide energy efficiency with high probability in a

randomly

deployed 3D network. In particular, we extend our previous routing method designed for 2D networks [3] to 3D networks. The proposed 3D routing method is a simple variation of 3D greedy routing and can guarantee energy efficiency of its paths with high probability in random 3D networks. We also study its asymptotic critical transmission radius to ensure the packet delivery with high probability in random 3D networks. Simulation results confirm our theoretical results.

This paper proposes a novel routing algorithm called AELAR for wireless sensor networks to meet QoS requirements: energy conservation and data delay reduction. Firstly, we propose a novel method of dividing routing request zone and construct a select equation which can enlarge the energy awareness as network time goes on. We make the routing request zone and factors in select equation changed automatically. Simulation results show that AELAR outperforms traditional algorithms in the performance of network lifetime, utilization and consumption balancing of energy and data delay.

Duty cycling technique is widely used in sensor networks to save energy. Due to coverage and other requirements, sensor nodes may have asynchronous duty schedules, which bring additional challenges for data collection. Existing approaches suffer from different limitations such as requirement of time synchronization. This paper proposed a cross-layer design, which utilizes multihop information to find shortcuts and reduces the delay in data collection.

RFID has been applied in many areas. Since the dense deployment of readers and tags, the collision problem of RFID system becomes a critical issue. In this paper, we introduce a novel probabilistic model to estimate the impact of reader to tag collision based on the information from physical layer. According to the theoretical analysis, our model ensures that more than one tag can be identified by both readers when they communicate with tags. To obtain the bit information, we employ the NI RFID emulator and LabView software. The simulation results show that the probability of miss-identification is lower than 17%.

Previous designed synchronization approaches advocate an

O

(1) search complexity. Although it is efficient, such an approach is vulnerable to

Desynchronization Attacks

, in which the secret information will become incrementally different between the tag and reader. Either adversary can utilize this to distinguish tags or the legitimate tag and reader cannot authenticate with each other. Even worse, synchronization approaches suffer from replay attacks. To address these problems, we propose a DESynchronization Tolerant RFID private authentication protocol, DEST, which forces a tag to keep its behaviors undistinguishable. DEST provides desynchronization tolerance, replay attack resistance, and forward secrecy. The analysis results show that DEST effectively enhances the privacy protection for RFID private authentication, and provides the same efficiency,

O

(1), as traditional synchronization approaches.

In recent years, wireless charging (a.k.a. wireless energy transferring) [3] has been recognized as a promising alternative to address the energy constraint challenge in wireless sensor networks. Comparing to the conventional energy conservation or harvesting approaches, wireless charging can replenish energy in a more controllable manner and does not require accurate location of or physical alignment to sensor nodes. In spite of these advantages, there has been little research on how much potential performance improvement may be achieved by applying the wireless charging approach to sensor networks and how to fully leverage its potential. In this paper, as one of the first efforts to study these issues, we (1) formulate the problem of maximizing the sensor network lifetime via co-determining routing and charging (ML-JRC), (2) prove the NP-hardness nature of the problem and derive an upper bound of the maximum sensor network lifetime that is achievable with ML-JRC, and (3) present a set of heuristics to determine the wireless charging strategies under various routing schemes, and demonstrate their effectiveness via in-depth simulation.

Wireless sensor networks (WSNs) have recently gained a great deal of research attention, with a wide range of applications being explored. In most applications, WSNs are deployed in inaccessible areas for a long lifetime. Software maintenance and update in WSNs are challenging. Network reprogramming is an important way to address this challenge. Code dissemination is a critical service to enable network reprogramming. Most code dissemination protocols employ segmentation and pipelining to improve the reprogramming efficiency. As we show in this paper, the choice of the page size in these segmented and pipelined dissemination protocols is of vital importance to the overall dissemination time. Hence, we explore the tradeoff in determining the optimal page size in terms of the overall dissemination time. We investigate the impact of page size for two typical code dissemination protocols in WSNs. Results show that the optimal page size decreases when the maximum hop count from the source node increases; and the optimal page size increases when the program size increases. The absolute value of the optimal page size is determined by the network scale, program image size, and protocol details.

It is a new challenge to provide priority-based delivery in low duty-cycled sensor networks where there are not always-awake communication paths and the wireless links are very time-varying and unreliable. In this paper, we propose a Dynamic Routing Algorithm for priority Guarantee(called DRAG) in low duty-cycled sensor networks. Both schemes of dynamic forwarding decision making and priority-based schedule are used in DRAG to achieve priority guarantee in low duty-cycled sensor networks. We evaluate DRAG via extensive simulations and the results show that DRAG can achieve good performance in delivery ratio and network delay.

Understanding device pair’s contacts is essential in pocket switched networks (PSN). However, most of the studies on this issue are focused on the empirical distribution aggregating inter-contact times from all the device pairs, and seeking to find common characteristics of their contact processes. In this paper, we present an insightful analysis on both the aggregated and the pair-wise inter-contact times obtained from three real-world datasets. We find that device pairs are heterogeneous in many aspects, including not only their contact frequencies, but also their contact patterns. More surprisingly, even for those frequently contacting pairs, their behaviors are diverse, and could not be described with a universal model. Finally, implication of the observed heterogeneity on PSN’s message forwarding algorithm is discussed, and we show that with the awareness of the device pair’s heterogeneous contact pattern, the network’s message relaying service could be improved considerably.

In this paper, delay minimization schemes for tree-based neighbor discovery in mobile robot networks are proposed and analyzed. Depending on the tree construction scheme, the expected value of neighbor discovery delay is changed. In our study, we focus on

M

-ary and

M

-Binary tree-based neighbor discovery. Regarding the number of neighboring robots,

M

-ary tree-based neighbor discovery has low but steady performance whilst

M

-Binary tree-based neighbor discovery shows better performance for optimal

M

. The simulation results provide performance comparisons of these schemes.

Target locating is a kernel and challenging function of many applications based on wireless sensor networks. Many existing approaches of target locating employ the binary detection model. In this paper, we first propose a probabilistic-based detection model for wireless sensor networks in a three-dimensional region, which is more realistic in reality. We further design a probability-based target locating algorithm and evaluate this algorithm under four typical deployment schemes of wireless sensor networks. Simulation results show that our simple and effective algorithm can locate the target and save much energy during the tracking process of a moving target.

In this paper, we study the interference analysis in a Nocoherent Frequency-Hopping (NC-FH) MFSK rural infrastructure Wireless Mesh Networks (WMNs) with each router node being equipped with multiple radio interfaces. Our choice of the FH/MFSK modulation technique here is not just to satisfy the security requirement in military communications but also to provide easy implementation for each router nodes; since FH/MFSK modulation technique has been specified in IEEE 802.11 standard, these router nodes can be implemented also using IEEE 802.11(FH) equipments. The performances of noncoherent slow frequency-hopping system with

M

-ary frequency-shift-keyed modulation (NC-FH/MFSK) with AWGN channel and Rician fading under independent multitone jamming (independent MTJ) are investigated in this paper. The expressions for calculating the exact BER performances of the system under the effect of the jamming strategies are derived. We apply the analyses to channel assignment (CA) in multiradio rural WMNs. We obtain a new interference model combining interfence tone and partial band noise, which would be incorporated into the CA algorithm to assign the most appropriate channel (or hopping pattern, in our case) to links in the mesh. Because it takes into account both the intra-network and the coexisting-network interferences, the new interference model thus reflects a very realistic interference situation in WMNs.

Gossiping is to broadcast the message of every node to all the other nodes in multi-hop wireless networks (MWNs). This operation plays an important role and is widely used in MWNs. Interference-aware gossiping scheduling (IAGS) aims to provide an interference-free scheduling for gossiping with the minimum latency. Previous work on IAGS mostly assumes that nodes are always active, and thus is not suitable for duty-cycled scenarios. In this paper, we investigate the IAGS problem in uncoordinated duty-cycled multi-hop wireless networks (IAGS-UDC problem) under protocol interference model and unbounded-size message model. We prove that the IAGS-UDC problem is NP-hard. We propose a novel approximation algorithm called MILD for this problem. The MILD algorithm achieves an approximation ratio of 3

β

2

(Δ + 6)|

T

|, where

β

is

$\lceil \frac{2}{3}(\alpha+2)\rceil$

,

α

denotes the ratio of the interference radius to the transmission radius, Δ denotes the maximum node degree of the network, and |

T

| denotes the number of time-slots in a scheduling period. Moreover, the number of transmissions scheduled by the MILD algorithm is at most 3 times as large as the minimum number of transmissions.

It has been long recognized that the interference among concurrent wireless transmissions plays a crucial role in limiting the performance of wireless networks. Recently, studies indicate that equipping nodes with multiple radios and operating these radios on multiple frequency channels can greatly enhance the capacity of wireless networks. On the other hand, to fully realize the benefits of multi-radio multi-channel communication, one may need to design an efficient channel assignment algorithm. In this paper, we study the channel assignment problem by proposing an algorithm that achieves load balancing Nash Equilibrium solution even in a selfish as well as topology-blind environment. Our simulation results also depict the effectiveness of the proposed channel assignment solution.

Noncontiguous OFDM (NC-OFDM) and Noncontiguous Spread OFDM (NC-SOFDM) have been proposed as two candidates for cognitive radio and dynamic spectrum access network. Since the available spectrum in cognitive radio system usually spreads through multiple non-contiguous spectrum holes, multi-carrier based transceivers need to deactivate some of their subcarriers to avoid interference to primary users. However, like OFDM and SOFDM, NC-OFDM and NC-SOFDM also suffer from large peak to average power ratio (PAPR). Hence, it is desired to analyze the PAPR performance of NC-OFDM and NC-SOFDM schemes with different spreading code sets. In this paper, we analyze the PAPR performance of NC-OFDM, NCSOFDM with binary Hadamard-Walsh spreading codes, and NCSOFDM with polyphase Carrier Interferometry (CI) spreading codes. Both analysis and simulation results show that the NCSOFDM with polyphase CI code set provides the lowest PAPR, while the NC-OFDM provides the highest PAPR and NC-SOFDM with Hadamard-Walsh code set in the middle.

The secure image coding scheme using compressed sensing (CS) is proposed and the secrecy of the scheme is explored. We verify that the CS-based coding scheme can provide a guarantee of secrecy by analysis and simulation. In our approach, random matrices are used as keys of decryption. Based on the feasibility of random symmetric signs matrices in compressed sensing, we obtain a theoretical result that the signal compressed sensing using sparse random binary matrices can be exactly recovered with high probability. Numerical results verify the theory and show matrices proposed in this paper perform equally to the prominent Gaussian matrices when measurement rate is higher than an equivalence threshold.

The broadcast nature of wireless transmissions is a two-edged sword for wireless broadcasting. On one hand, it makes broadcasting much more efficient; on the other hand, it causes concurrent transmissions much more likely to collide, deteriorating throughput and delay. In this paper, we propose a novel PHY layer technique called

onion decoding

, which enables correct decoding of two or more colliding transmissions. Thus, more concurrent transmissions can be scheduled, leading to improved throughput and delay. As we shall see in the paper, achieving optimal broadcast throughput and delay, with and without onion decoding, are non-trivial in multi-rate wireless networks. No efficient algorithm is known. We propose a simple heuristic algorithm for wireless broadcasting using onion decoding, and evaluate its performance through simulations. Simulation results confirm that onion decoding can significantly improve throughput and delay of wireless broadcasting.

This paper considers spectrally efficient anti-jamming system design based on message-driven frequency hopping (MDFH). Unlike conventional FH where the hopping frequencies are determined by a preselected pseudonoise (PN) sequence, in MDFH, part of the message acts as the PN sequence for carrier frequency selection. It is observed that MDFH has high spectral efficiency and is particularly robust under strong jamming. However, disguised jamming from sources of similar power strength can cause performance losses. To overcome this drawback, in this paper, we propose an anti-jamming MDFH (AJ-MDFH) system. The main idea is to transmit a secure ID sequence along with the information stream. The ID sequence is generated through a cryptographic algorithm using the shared secret between the transmitter and the receiver. It is then exploited by the receiver for effective signal detection and extraction. It is shown that AJ-MDFH can effectively reduce the performance degradation caused by disguised jamming. Moreover, AJ-MDFH can be extended to a multi-carrier scheme for higher spectral efficiency and/or more robust jamming resistance. Simulation example is provided to demonstrate the performance of the proposed approaches.

Ensuring the security of RFID’s large-capacity database system by depending only on existing encryption schemes is unrealistic. Therefore, data sharing for security management to supplement it is drawing attention as an extremely secure scheme. However, applying the existing secret sharing scheme to this method makes the size of the share equal to that of the original data. Thus, it is not suitable for application to large-scale database. This paper proposes secret sharing algorithms that enable efficient data sharing security management based on the characteristics of the All-Or-Nothing Transform encryption mode. The proposed algorithms enable fast sharing and reconstruction in terms of processing speed and allow the sum of shares to be equal to that of the plaintext, thereby making them suitable for large-capacity database storage.

This study proposes an approach to deploy a node implementing IDS (Intrusion Detection System) in MANETs for detecting and isolating wormhole nodes, if they exist. This study uses ns2 to evaluate the proposed IDS nodes, and the results show that these IDSs can rapidly and correctly block the wormhole nodes under the circumstances of low false positives.

A publicly verifiable public key encryption scheme has the property that the validity of ciphertexts can be verified without knowledge of private key, which facilitate its non-interactive threshold decryption. Based on a selective identity secure IBE by Boneh et. al, a new publicly verifiable encryption scheme is presented using two hash functions. We prove the IND-CCA2 security of the new scheme under decisional BDHI assumption and target collision resistant property of two hash functions. Furthermore, our scheme has very short public and private keys that are independent of the security parameter, witch significantly simplifies public key certificate management and reduces the computation cost for encryption or decryption.

The astronautics oriented computer simulation has two remarkable characteristics: one is the high dynamics of the simulation scenario; the other is the huge quantity of computing. To meet the above two requirements in complex scenario simulating computing (such as constellation optimization, resource scheduling and space-based early warning, et al), we developed an astronautics simulation and cluster computing environment. We employed distributed clusters as the computing environment to increase it’s numerical calculation ability and controllability, and we developed it based on High Level Architecture to enhance it’s dynamic simulation adaptation. The organization algorithm of the distributed clusters is mainly discussed in this paper. We provided an self-organization algorithm based on wireless or connectionless communication protocol.

A strongly partitioned operating system model for data link (DL) networks is proposed. Every partition is completely independent and isolated in this model. A fault in one partition only affects the partition itself rather than other partitions. The operating system kernel, called DL-OS, is discussed in sub-topics including system architecture, partition scheduling, task model, inter-partition communication and memory management. DL-OS is analyzed and evaluated. DL-OS is applied in a DL network, in which the traditional three systems were integrated into only one platform. The size, weight and power (SWAP) of the DL network terminal is dramatically decreased.

In this paper, we consider the security of twin Hybrid ElGamal (

THEG

) scheme when instantiated over the group of signed quadratic residues. In random oracle model, the scheme is proved

IND

-

CCA

secure under composite computation Diffie-Hellman assumption, which is at least as hard as factoring. In the standard model, we give a more tight security reduction for

THEG

, using a new hash proof system, than that of Hybrid ElGamal (

HEG

) in [4]. Therefore,

THEG

can be instantiated over smaller RSA modulus than

HEG

, which results in shorter ciphertexts for the same bit security and hence reduces the communication complexity of encrypted data transmitted over public communication lines.

This paper designs a fair message collection scheme on the grid-style wireless network, aiming at accelerating the fast and stable deployment of smart grid systems. Based on the slot-based medium access protocol, the proposed scheme allocates extra slots on each control round for the nodes along the fringe of the grid, as they unavoidably have poor delivery ratio due to long hops from the coordinator. Along the fringe path, the farther away from the coordinator, the higher priority a node has for message loss compensation. The simulation results, obtained from a discrete event scheduler, show that we can achieve up to 15.6 % improvement of delivery ratio for the farmost node and 12.3% reduction of standard deviation, with 14.3 % extension of control loop length.

Multipath routing has been employed to improve the network throughput, to provide load balance and to achieve reliability for many years in both wired and wireless networks. In wireless networks, the communication cost of the multipath construction scheme is at least polynomial. In this paper, we focus on the problem of how to chose a right position to deploy a wireless sensor node such that the existence of

K

multipaths, which connect a wireless sensor node and the data sink, is guaranteed. Traditionally, at a given position, the communication cost of the multipath existence checking is at least polynomial through using a multipath construction scheme. To reduce the communication overhead, we propose a simple and efficient multipath existence checking scheme, which incurs only a constant communication overhead.

This paper proposes a data collection scheme for the two-tier vehicle sensor network, which is comprised of high-speed WLANs surrounded by the ubiquitous cellular network, aiming at improving the accuracy and speed of event detection out of bunch of sensor data. Each vehicle reports periodically summary data including its location, timestamp, and alarm data via the cellular network, while it sends whole set, entering the WLAN range. For event detection, the information server locates the vehicles whose data must be further investigated according to the legacy spatio-temporal query or the trajectory comparison method. The WLAN can give precedence to the vehicle which might have the important data by operating two different frequencies. We are currently refining this framework and planning to test in Jeju area.

In the emerging energy efficient framework, power allocation for ultra wide band (UWB) is much significant given its extremely large bandwidth. For multi-band UWB, this area has been extensively researched in the context of OFDM resources allocation. For pulse-based UWB, however, there is still an urgent need for efficient waveform design technique to embody arbitrary power allocation strategy. In this paper, we present a UWB waveform design method based on the radius basis network neural networks (RBF). The power density spectrum of emitted waveform is firstly abstract to a general mathematic function. Then based on the interpolation theory, RBF network is adopted to generate UWB waveforms given any spectrum shape. Numerical simulations validate our algorithms through the water filling (WF) waveforms shaping.

The purpose of this paper is threefold. First, it briefly introduces basic Bayesian techniques with emphasis on present applications in sensor networks. Second, it reviews modern Bayesian simulation methods, thereby providing an introduction to the main building blocks of the advanced Markov chain Monte Carlo and Sequential Monte Carlo methods. Lastly, it discusses new interesting research horizons.

Attributed to complex and dynamic propagations in underwater acoustic sensors network, the multipath signals has posed great challenges in the receiver designing in past decades of years. In this paper, we adopt the UWB channel model in underwater networks and suggest a blind non-coherent receiver. Some differentiated features have been developed to represent the multipath signals. Then, we formulate the underwater signal detection as a data mining process. Fuzzy c-means clustering (FCM) algorithm is finally adopted to perform blind signal detection. Numerical simulations show that our scheme outperforms the traditional noncoherent techniques.

Relay is considered as a method to ensure capacity and coverage in the broadband wireless access (BWA) system. This paper proposes a type of MAC layer simulator architecture for the relay enhanced BWA networks, and then addresses the issue on the network topology when relay is introduced. Furthermore, downlink co-operative communication in such relay scenario is discussed on. The results show that the proposed relay enhanced BWA system outperforms the single-hop one on spectrum efficiency.

Exploiting the rich multipath of ultrawideband (UWB) system with channel estimating for Rake receivers is a key point to achieve high performance. This paper presents an improved approach of channel estimation for pulse UWB communication system based on the theory compressed sensing (CS). The Matching Pursuit algorithm is used to identify the channel taps under the compressed sensing framework with prior knowledge of the power delay profile (PDP) of the channel. The MP algorithm itself is also modified to achieve higher performance of estimation based on the principle of probabilistic MP (PMP). Simulation results show that the proposed approach outperforms the already existing CS-MP channel estimation scheme.

Using Singular Value Decomposition (SVD), we develop an algorithm for signal recovery in compressive sensing. If the signal or sparse basis is properly chosen, an accurate estimate of the signal could be obtained by a simple and efficient signal recovery method even in the presence of additive noise. The theoretical and simulation results show that our approach is scalable both in terms of number of measurements required for stable recovery and computational complexity.

Future cognitive radios will be capable of scanning a wide band of frequencies, in the order of a few GHz, and the employment of adaptive wave-forms according to the estimated spectrum of the licensed systems challenges traditional spectral estimation methods, which typically operate at or above Ny-quist rates. We research the problem of estimating the spectrum of the wide-band signal received at the cognitive radio sensing receiver using compressed sensing coupled with interference temperature estimation to determine the spectrum occupancy of the licensed system. First, we achieve coarse identifica-tion of frequency boundaries of each sub-band via compressed sensing tech-niques at a Sub-Nyquist rate, which is much less than Nyquist rate. Then we use MTM-SVD method to compute the interference temperature value of each sub-band, and compare these values with threshold. The multitaper spectrum esti-mation has high accuracy and near-optimality. And the simulation result shows that we can achieve the interference temperature estimation of each sub-band accurately.

Compressive sensing/sampling (CS) has been one of the most active research in signal and image processing since it was proposed. The importance of CS is that it provides a high performance sampling theory for sparse signals or signals with sparse representation. CS has shown outstanding performances in many applications. In this paper we discuss two potential applications of CS in radio astronomy: image deconvolution and Faraday rotation measure synthesis. Both theoretical analysis and experimental results show that CS will bring radio astronomy to a brand new stage.

Compressive sensing(CS) is an emerging filed based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-Nyquist signal acquisition. One challenging problem in compressive sensing is that it is difficult to represent signal in sparse basis, which makes this algorithm sometimes impractical. In this paper, we can setup a new standard compressive sensing problem for autoregressive hidden markov signal by utilizing the original observation vector and the autoregressive coefficients.