This PDF file contains the front matter associated with SPIE Proceedings Volume 9103, including the Title Page, Copyright information, Table of Contents, Invited Panel Discussion, and Conference Committee listing.

Digital filters are a basic building block of a communication system and can serve many diverse purposes such as: restricting a signal to a prescribed frequency band, separating a signal into two or more sub-bands, modifying the spectral content of a signal, modeling a communication channel, performing mathematical operations, reducing the noise content of a signal, etc. On occasion, digital filters are used to estimate the bandwidth of a digital modulation and this paper will investigate possible issues that can be encountered when using digital filters for this purpose.

Continuous Phase Modulation (CPM) schemes are advantageous for low-power radios. The constant envelope transmit signal is more efficient for both linear and non-linear amplifier architectures. A standard, coherent CPM receiver can take advantage of modulation memory and is more complex than a coherent Phase Shift Keyed receiver. But the CPM signal can be demodulated non-coherently and still take advantage of the trellis structure inherent in the modulation. Prior analyses of several different non-coherent CPM schemes have been provided with many providing coherent or near coherent performance. In this paper we will discuss a new, reduced complexity decoder that improves upon the noncoherent performance. In addition, this new algorithm generates soft decision metrics that allow the addition of a forward error correction scheme (an outer code) with coherent equivalent performance gains.

The shift to a full information-centric paradigm in the battlefield has allowed ConOps to be developed that are only possible using modern network communications systems. Securing these Tactical Networks without impacting their capabilities has been a challenge. Tactical networks with fixed infrastructure have similar vulnerabilities to their commercial counterparts (although they need to be secure against adversaries with greater capabilities, resources and motivation). However, networks with mobile infrastructure components and Mobile Ad hoc Networks (MANets) have additional unique vulnerabilities that must be considered. It is useful to examine Tactical Network based ConOps and use them to construct a threat model and baseline cyber security requirements for Tactical Networks with fixed infrastructure, mobile infrastructure and/or ad hoc modes of operation. This paper will present an introduction to threat model assessment. A definition and detailed discussion of a Tactical Network threat model is also presented. Finally, the model is used to derive baseline requirements that can be used to design or evaluate a cyber security solution that can be scaled and adapted to the needs of specific deployments.

This paper proposes a novel signal analysis based node localization strategy for sensor networks used in structural health monitoring (SHM) applications. The key idea is to analyze location-dependent multipath signal patterns in inter-node ultrasonic signals, and use machine-learning mechanisms to detect such patterns for accurate node localization on metal substrates on target structures. Majority of the traditional mechanisms rely on radio based Time Delay of Arrival (TDOA), coupled with multilateration, and multiple reference nodes. The proposed mechanism attempts to solve the localization problem in an ultrasonic sensor network (USN), avoiding the use of multiple reference beacon nodes. Instead, it relies on signal analysis and multipath signature classification from a single reference node that periodically transmits ultrasonic localization beacons. The approach relies on a key observation that the ultrasonic signal received at any point on the structure from the reference node, is a superposition of the signals received on the direct path and through all possible multi-paths. It is hypothesized that if the location of the reference node and the substrate properties are known a-priori, it should be possible to train a receiver (source node), to identify its own location by observing the exact signature of the received signal. To validate this hypothesis, steps were taken to develop a TI MSP-430 based module for implementing a run-time system from a proposed architecture. Through extensive experimentation within an USN on the 2024 Aluminum substrate, it was demonstrated that localization accuracies up to 92% were achieved in the presence of varying spatial resolutions.

Many recent research efforts have confirmed that, given the natural evolution of telecommunication systems, they can be approached by a new modeling technique, not based yet on traditional approach of graphs theory. The branch of complex networking, although young, is able to introduce a new and strong way of networks modeling, nevertheless they are social, telecommunication or friendship networks. In this paper we propose a new modeling technique applied to Wireless Sensor Networks (WSNs). The modeling has the purpose of ensuring an improvement of the distributed communication, quantifying it in terms of clustering coefficient and average diameter of the entire network. The main idea consists in the introduction of hybrid Data Mules, able to enhance the whole connectivity of the entire network. The distribution degree of individual nodes in the network will follow a logarithmic trend, meaning that the most of the nodes are not necessarily adjacent but, for each pair of them, there exists a relatively short path that connects them. The effectiveness of the proposed idea has been validated thorough a deep campaign of simulations, proving also the power of complex and small-world networks.

Domestic environment and human interaction with services supplied by domotic devices is going to be a very interesting application field. With a domotic system is possible to achieve great interaction between human beings, environments and smart devices. The enhancing of these interactions is the main goal of this work whose intent is to improve the classic concept of domotics. The framework we developed can be used for several application fields such as lighting, heating, conditioning or water management and energy consumption. In particular, the proposed system can optimize energy consumptions by rising awareness to users that have full control of their house and the possibility to save money and reduce the impact of the energetic consumes to the earth, matching the new "green" motto requirements. In this way, the overall system wants to match the central concept of Internet Of Things (IoT) as well. From this point of view a complex automation system with smart devices make possible a more efficient way to produce, follow and manage domotic policies. Following the spread of IoT, for this work we designed and implemented new plug-and-play and ready-to-use smart devices that are part of a complex automation system that offers a user-friendly web application and allows users to control and interact with different plans of their house in order to make life more comfortable and be aware of their energy consumptions. Control and awareness arc the two key points that led us to develop the proposed system.

Dynamic Spectrum Access, which through its ability to adapt the operating frequency of a radio, is widely believed to be a solution to the limited spectrum problem. Mobile Ad Hoc Networks (MANETs) can extend high capacity mobile communications over large areas where fixed and tethered-mobile systems are not available. In one use case with high potential impact cognitive radio employs spectrum sensing to facilitate identification of allocated frequencies not currently accessed by their primary users. Primary users own the rights to radiate at a specific frequency and geographic location, secondary users opportunistically attempt to radiate at a specific frequency when the primary user is not using it. We quantify optimal signal detection in map based cognitive radio networks with multiple rapidly varying phase changes and multiple orthogonal signals. Doppler shift occurs due to reflection, scattering, and rapid vehicle movement. Path propagation as well as vehicle movement produces either constructive or destructive interference with the incident wave. Our signal detection algorithms can assist the Doppler spread compensation algorithm by deciding how many phase changes in signals are present in a selected band of interest. Additionally we can populate a spatial radio environment map (REM) database with known information that can be leveraged in an ad hoc network to facilitate Dynamic Spectrum Access. We show how topography can help predict the impact of multi-paths on phase change, as well as about the prediction from dense traffic areas. Utilization of high resolution geospatial data layers in RF propagation analysis is directly applicable.

Nowadays one of the main task of technology is to make people's life simpler and easier. Ambient intelligence is an emerging discipline that brings intelligence to environments making them sensitive to us. This discipline has developed following the spread of sensors devices, sensor networks, pervasive computing and artificial intelligence. In this work, we attempt to enhance the Internet Of Things (loT) with intelligence and environments exploring various interactions between humans' beings and the environment they live in. In particular, the core of the system is composed of an automation system, which is made up with a domotic control unit and several sensors installed in the environment. The task of the sensors is to collect information from the environment and to send them to the control unit. Once the information is collected, the core combines them in order to infer the most accurate human needs. The knowledge of human needs and the current environment status compose the inputs of the intelligence block whose main goal is to find the right automations to satisfy human needs in a real time way. The system also provides a Speech Recognition service which allow users to interact with the system by their voice so human speech can be considered as additional input for smart automatisms.

In this paper, a high-dimensional detection problem of single input single output (SISO) spread OFDM system is attempted using low complexity approach. A combination of signal processing procedures is introduced to provide a low complexity detection algorithm with improved performance compared to existing linear detectors such as Minimum Mean Square Error (MMSE). Soft output MMSE is implemented first to provide a reliability measure of all bits in the received vector using an approximated Log Likelihood Ratio (LLR) information. The most reliable bits are deemed correctly received and the least reliable bits undergo Branch and Bound (BB) detection process in a sequential manner. Within this block of unreliable bits, BB starts with the most unreliable bits and then the second most unreliable bits and so on. Simulation results show that the proposed technique provides improved performance with a significant reduction in the computational complexity.

We propose a new structure of Space-Time codes of which the decoding problem can be decomposed into multiple one-dimensional closest-point search. The search can be accomplished by a simple rounding method. The new coding technique can be applied to data transmission of sensor systems, where the decoding task is expected to be quickly accomplished for the purpose of fast response.

Coprime array, which utilizes a coprime pair of uniform linear subarrays, is an attractive structure to achieve sparse array configurations. Alternatively, effective coprime array configurations can be implemented using a uniform linear array with two coprime sensing frequencies. This enables the integration of the coprime array and filter concepts to achieve high capabilities in meeting system performance and complexity constraints. This paper examines its performance for direction-of-arrival estimations. In particular, we analyze the number of detectable signals and the estimation accuracy as related to the array configurations and sensing frequencies.

A planar antenna array based feature detection scheme is proposed to estimate the directional, location and modulation information pertaining to radio sources in a cognitive radio environment. The proposed system employs multiple direction estimation stations and a fusion station. Planar antenna arrays and three-dimensional (3-D) infinite impulse response (IIR) digital filters are employed to perform volume scanning of the radio environment, leading to a spatial power profile, which is subjected to peak detection in order to estimate the direction of arrival corresponding to each source. Cyclosationay feature detection is then performed along each direction to estimate the frequency and modulation information. Two simulation examples are provided to verify the feasibility of the proposed approach.

New applications in wireless environments are increasing and keeping even more interests from the developer companies and researchers. In particular, in these last few years the government and institutional organization for road safety spent a lot of resources and money to promote Vehicular Ad-Hoc Network (VANET) technology, also car manufactures are giving a lot of contributions on this field as well. In our paper, we propose an innovative system to increase road safety, matching the requests of the market allowing a cooperation between on-board devices. The vehicles are equipped with On Board Unit (OBU) and On Board Radar Unit (OBRU), which can spread alerting messages around the network regarding warning and dangerous situations exploiting IEEE802.llp standard. Vehicles move along roads observing the environment, traffic and road conditions, and vehicles parameters as well. These information can be elaborated and shared between neighbors, Road Side Unit (RSU)s and, of course, with Internet, allowing inter-system communications exploiting an Road Traffic Manager (RTM). Radar systems task it the detection of the environment in order to increase the knowledge of current conditions of the roads, for example it is important to identify obstacles, road accidents, dangerous situations and so on. Once detected exploiting onboard devices, such as Global Position System (GPS) receiver it is possible to know the exact location of the caught event and after a data elaboration the information is spread along the network. Once the drivers are advised, they can make some precautionary actions such as reduction of traveling speed or modification of current road path. In this work the routing algorithms, which have the main goal to rapidly disseminate information, are also been investigated.

Sensors capable of measuring the quasi-electrostatic field of traveling projectiles have been developed to detect the passage of a bullet in flight. These sensors provide an alternative to existing optical chronograph technologies, which are sensitive to variations in environmental lighting, and magnetic chronographs, which require close proximity to the bullet’s path. In contrast, electric field sensors are insensitive to lighting changes and prior testing has demonstrated the ability to reliably detect bullets at distances of at least three meters. A linear array of these sensors has been used to measure the time of flight between the sensors, which with the known distance between the sensors can be used to calculate the projectile’s velocity. These velocity measurements are compared to established chronograph technology as a measurement validation. By extending this array of sensors along the projected path of the projectile, a profile of the projectile’s position and velocity through flight can be calculated. This expected utility of this data is in refining the calculations that are performed to determine a ballistic solution, particularly in long range engagements, where there has been limited availability of accurate projectile velocity measurements. This robust sensor array that can easily be deployed represents an inexpensive way to experimentally investigate numerous phenomena related to ballistics modeling.

Correlative interferometric imaging from sensor arrays relies on reconstructing source intensity by using the cross-correlation across near-field or far-field measurements from multiple sensor elements. Often the reconstruction problem is ill-posed resulting in unrealistic reconstructions of signals and images. This paper examines the consequences of using extremal entropy metrics in the reconstruction. These range from inducing sparsity to the closer conformance of the reconstruction boundaries to the support of the actual signal source. Situations involving far-field interferometric imaging of extended sources are considered and experimental results are provided.

This paper visits the application of single-source noise reduction on received audio over a HF channel. The noise reduction algorithm is typically used in vocoder noise processing at the transmitter before encoding. This study presents the results of the algorithm effects by objectively measuring audio quality through the use of industry standard PESQ analysis.

Nowadays the focus on power consumption represent a very important factor regarding the reduction of power consumption with correlated costs and the environmental sustainability problems. Automatic control load based on power consumption and use cycle represents the optimal solution to costs restraint. The purpose of these systems is to modulate the power request of electricity avoiding an unorganized work of the loads, using intelligent techniques to manage them based on real time scheduling algorithms. The goal is to coordinate a set of electrical loads to optimize energy costs and consumptions based on the stipulated contract terms. The proposed algorithm use two new main notions: priority driven loads and smart scheduling loads. The priority driven loads can be turned off (stand by) according to a priority policy established by the user if the consumption exceed a defined threshold, on the contrary smart scheduling loads are scheduled in a particular way to don’t stop their Life Cycle (LC) safeguarding the devices functions or allowing the user to freely use the devices without the risk of exceeding the power threshold. The algorithm, using these two kind of notions and taking into account user requirements, manages loads activation and deactivation allowing the completion their operation cycle without exceeding the consumption threshold in an off-peak time range according to the electricity fare. This kind of logic is inspired by industrial lean manufacturing which focus is to minimize any kind of power waste optimizing the available resources.

McQ has developed a wireless, time-synchronized, event control system to control, monitor, and record events with precise timing over large test sites for applications such as high speed rocket sled payload testing. Events of interest may include firing rocket motors and launch sleds, initiating flares, ejecting bombs, ejecting seats, triggering high speed cameras, measuring sled velocity, and triggering events based on a velocity window or other criteria. The system consists of Event Controllers, a Launch Controller, and a wireless network. The Event Controllers can be easily deployed at areas of interest within the test site and maintain sub-microsecond timing accuracy for monitoring sensors, electronically triggering other equipment and events, and providing timing signals to other test equipment. Recorded data and status information is reported over the wireless network to a server and user interface. Over the wireless network, the user interface configures the system based on a user specified mission plan and provides real time command, control, and monitoring of the devices and data. An overview of the system, its features, performance, and potential uses is presented.

The FSO (Free Space Optics) communication uses the visible or infrared light for transmission. As well as cable optics FSO also uses laser for the data transmission, but the data flow is not transmitted in the fiber but in the air. This technology does not require expensive fiber optic cables and or ensure the licensing zone as it is in the case of radio networks. As well as in the cable transmissions are different modulations used. Nowadays, the most used modulations are QAM and OFDM. OFDM belongs to the border group of modulations with more carrier waves, where the information's are transmitted via subcarrier waves with lower data flow and baud rate. It is mainly used in broadband wire and wireless communications. OFDM provides very high signal resistance against the interference, chromatic dispersion (CD) and polarization mode dispersion (PMD)[l]. Modulation method involves the use of several hundreds to thousands of subcarrier waves. QAM is a composite modulation, which uses for symbol creation the combination of ASK (Amplitude Shift Keying) and PSK (Phase Shift Keying). Each state is represented by a specific value of the amplitude and phase. It's actually multistate modulation, which is able to transmit n bits by m symbols. That means that more bits are transferred at one moment. This paper deals with the modulations used in FSO. Most used modulation in FSO is OOK (On-Off Keying) , but modulations OFDM and QAM are (modulation ) ways of the future. The main task was to determine how much is the reach of modulations changing with the changes of density (visibility) of fog and the set transceiver power. As software environment for simulations has been used OptiSystem program. For the simulation of the atmosphere the FSO component has been used. In this component were simulated attenuations, which are responding to varying densities of fog [2]. At different intensities of fog were changing the received power.