Cryptography \tPublic Key and Private Key Cryptography Discussion on use of private and public keys for cryptography applciactions. \tCounter with Cipher Block Chaining-Message Authentication Code (CCM) IP Core Hardware/Firmware implementation of the Counter with Cipher Block Chaining-Message Authentication Code (CCM) using Advanced Encryption Standard (AES) Encryption Block. Fully functional and synthesizable VHDL CCM IP core. \tAdvanced Encryption Standard (AES) IP Core Hardware/Firmware implementation of the Advanced Encryption Standard (AES). Fully functional and synthesizable VHDL AES IP core. \tSecure Faxing with JPSEC Faxing documents using Secure JPEG 2000, also referred to as JPSEC, is a method to secure image contents with stronger encryption and data integrity than what is provided by T.30. \tDocument Signature by Multiple Parties This page describes a method to allow multiple users to simultaneously sign a document using fax and Internet technologies. Either digital or physical signatures may be used to sign the document. Networking \tMulticast and Unicast Streaming Media A discussion of the differences between unicast and multicast transmission of multimedia. \tDynamic Directional RTS/CTS A beamforming based addition to the RTS/CTS protocol which can improve overall network throughput. \tTCP TURN Discussion of TCP with Traversal using Relay NAT. \tSTUN Server in ICE Context How ICE clients use STUN for NAT discovery and traversal. \tICE: Interactive Connectivity Establishment Discussion of how ICE clients handle NAT discovery and traversal for VoIP applications. \tTCP TURN \t802.11 Authentication and Association A description of the Authentication and Association Procedures in 802.11. \tDistortion Based Networking – Ad Hoc Wireless Routing When there are errors in multimedia data, these errors are able to be perceived by the end user in the form of distortion. This motivates us to choose a routing protocol based on the parameters which affect distortion such as delay and packet drops. \tNetworking Nearly every organization utilizes some form of networking to accomplish their goal. Because of the many topologies and scenarios available, it is important to properly choose the correct networking protocols to fit a given need. \tDistortion Minimizing Rate Control for Wireless Multimedia Sensor Networks Video transmission over wireless networks needs to be treated differently than standard data transmission. A distortion minimizing rate control (DMRC) rather than TCP can help to both maintain fairness among different streams while keeping data rate consistent. \tNetwork Utility Maximization (NUM) for Resource Allocation We introduce network utility maximization (NUM) or layering as optimized decomposition as an approach to optimizing layeres data communications networks. \tIEEE 802.11e An introduction to IEEE 802.11e Standard. \tIEEE 802.11n An introduction to IEEE 802.11n Standard. \t802.11 Distributed Coordination Function (DCF) The basic functionality of the 802.11 distributed coordination function (DCF) is explained. Concepts, including the hidden/exposed terminal problem and the network allocation vector, are explained in more detail. WebRTC \tEstablishing a WebRTC Media Session A discussion of establishing media sessions between WebRTC endpoints. \tWebRTC Communications Security A discussion of protocols used to implement WebRTC security. \tWebRTC and Complete Call Security A discussion of call security considerations for WebRTC. \tWebRTC and VOIP Compatibility A discussion of communications security considerations between VoIP and WebRTC endpoints. \tWebRTC Gateways A discussion of using gateways to support WebRTC sessions. \tWebRTC Enabled VoIP Endpoints A discussion of enabling VoIP endpoints to communicate with WebRTC endpoints directly. \tWebSockets and SIP over WebSockets A discussion of WebSockets protocol to support WebRTC browser to browser communications. Compressed Sensing \tSecrecy of Cryptography With Compressed Sensing The secrecy of images encoded using compressed sensing is examined. The standard deviation of the guessed sampling matrix is calculated and the impact this has on the security of the image is explored. \tCompressed Sensing in JPSEC Compressed sensing (CS) can be used as the encryption mechanism within the JPSEC protocol. The inherent properties of CS allow for some desirable properties within an image encryption scheme. \tMultipath Channel Estimation with Compressed Sensing We propose a method for using compressed sensing (CS) to find the multipath channel coefficients in a sparse channel. The channel is sensed using a pseudo-random process and the coefficients are determined using l1 minimization techniques. \tRecovery of Audio Signals with Compressed Sensing A method is presented by which analog audio signals can be directly sampled and compressed, resulting in decreased complexity and storage requirements for sparse wideband signals. \tInterference Cancellation in Compressed Sensed Signals A method is presented by which, for two compressed sensed signals, a signal of interest can be separated from an interferer based on some assumptions about the signals. \tAdaptive Parity Error Detection for Compressive Imaging Traditional image compression is very sensitive to bit errors from a lossy channel. By using compressed sensing to compress an image, the error resiliency of an encoded image is greatly increased. \tNoise Resiliency with Compressed Sensing Noise Resiliency with Compressed Sensing. \tError Correction Using Compressed Sensing Techniques Discussion on how compressed sensing techniques can be used for forward error correction. \tGradient Projection Reconstruction of Compressed Sensing Signals A gradient projection algorithm is introduced with the intention of decreasing the computational complexity of the compressed sensing reconstruction problem. Particle Swarm Optimization \tAdaptive Antenna Arrays using Particle Swarm Optimization Adaptive Antenna Arrays using Particle Swarm Optimization. \tParticle Swarm Optimization on FPGA Particle Swarm Optimization on FPGA. \tTime Delay of Arrival (TDOA) using Particle Swarm Optimization (PSO) An application of swarm coding to localization using time-delay of arrival. \tParticle Swarm Optimization (PSO) in the RWA Process for All-Optical WDM Networks Particle Swarm Optimization is used to determine the optimal Routing and Wavelength Assignment for an all optical Wavelength Division Multiplexing network. \tBlind Signal Separation (BSS) using Particle Swarm Optimization (PSO) A method of designing adaptive unmixing filters for BSS by using PSO to determine optimal coefficients. \tParticle Swarm Optimization (PSO) in the Grassmannian Line Packing Problem for MIMO Beamforming Use of Particle Swarm Optimization to solve the Grassmannian line packing problem for the offline design of MIMO codebooks. \tGaussian Particle Swarm Optimization (GPSO) A PSO based algorithm using Gaussian random variables that is designed to not get caught in local minima. \tEuclidean Particle Swarm Optimization (EPSO) A PSO based algorithm that uses Euclidean distance as a measure of convergence to help prevent convergence to a local minima. \tAdaptive Particle Swarm Optimization (APSO) A modification of PSO that is designed to deal with real time changing data by reevaluating particles to test for changes. \tParticle Swarm Optimization (PSO) in Signal Separation A PSO based algorithm for reducing noise in speech signals based upon optimizing the effects of a Singular Value Decomposition. \tAdapting Particle Swarm Optimization (PSO) by Deciding on the State of Convergence An algorithm is presented for deciding on the state of convergence of PSO and, based on this, adapting its parameters appropriately.