Abstract: A system and method for converting a non-cognitive radio into a cognitive radio is presented. A cognitive radio system includes, a non-cognitive radio; an electronic device, a spectrum sensing logic and configuration and management logic. The electronic device is connected to the non-cognitive radio so that it receives and/or transmits messages to/from a wireless network. The configuration and management logic is connected between the non-cognitive radio and the spectrum sensing logic. The spectrum sensing logic and the configuration and management logic are removable from the non-cognitive radio allowing the cognitive radio to operate in a non-cognitive mode. The spectrum sensing logic senses a wireless environment to determine available frequencies and available channels. The configuration and management logic transmits available frequencies, available channels or other spectrum data to a remote spectrum manager that is managing access to the wireless network.

Abstract: A method is disclosed to detect a broad class of signals in Gaussian noise using higher order statistics. The method detects a number of different signal types. The signals may be in the base-band or the pass-band, single-carrier or multi-carrier, frequency hopping or non-hopping, broad-pulse or narrow-pulse etc. In a typical setting this method provides an error rate of 3% at a signal to noise ratio of 0 dB. This method gives the time frequency detection ratio which may be used to determine if the detected signal falls in Class Single-Carrier of Class Multi-Carrier. Additionally, this method may be used for a number of different applications such as multiple signal identification, finding the basis functions of the received signal.

Abstract: An algorithm to detect a broad class of signals in Gaussian noise using higher-order statistics. The algorithm detects a number of different signal types. The signals may be in the base-band or the pass-band, single-carrier or multi-carrier, frequency hopping or non-hopping, broad-pulse or narrow-pulse etc. In a typical setting this algorithm provides an error rate of 3/100 at a signal to noise ratio of 0 dB. This algorithm gives the time frequency detection ratio that may be used to determine if the detected signal falls in Class Single-Carrier of Class Multi-Carrier. Additionally this algorithm may be used for a number of different applications such as multiple signal identification, finding the basis functions of the received signal and the like.

Abstract: A method and system are disclosed to detect a broad class of signals including Advanced Television Systems Committee (ATSC) digital television (DTV) and wireless microphone signals. This signal detection method performs in Gaussian noise, employing Higher Order Statistics (HOS). Signals are processed in time and frequency domains as well as by real and imaginary components. The spectrum sensing employed also supports Denial of Service (DoS) signal classification. The method can include parameters that may be tailored to adjust the probability of detection and false alarm.

Abstract: A system and method for the operation of a Spectrum Manager (SM) within a cognitive radio system includes two primary states of operation: SM at network initialization and SM at network operation. While in the network Initialization state, the SM's primary responsibility is to find an operating channel. After an operating channel is found, the SM moves from the network initialization state to the network operation state while executing a procedure to establish a network. While in the network operation state, the SM can execute other procedures, a procedure to update list of available channel from the incumbent database of channel and frequency data, a procedure to determine a signal type, a procedure to enter co-existence mode, deciding when to move to a backup channel and issuing calls for the same as well as background procedures such as looking for better backup channels when the SM is otherwise idle.

Abstract: In some embodiments, authentication, confidentiality, and privacy are enhanced for a wireless network of cognitive radios by encryption of network management and control messages as well as data traffic, thereby protecting information pertaining to node identification, node location, node-sensed incumbent transmissions, CRN frequency channel selections, and such like. During initial network registration, a temporary ID can be issued to a node, and then replaced once encrypted communication has been established. This prevents association of initial, clear-text messages with later encrypted transmissions. Elliptic curve cryptography can be used for mutual authentication between subscribers and the base station. ECC-based implicit digital certificates can be embedded in co-existence beacons used by CRN nodes to coordinate use of frequency channels, thereby preventing denial of service attacks due to transmitting of falsified beacons.

Abstract: An algorithm system to detect a broad class of signals in Gaussian noise using higher-order statistics. The algorithm system detects a number of different signal types. The signals may be in the base-band or the pass-band, single-carrier or multi-carrier, frequency hopping or non-hopping, broad-pulse or narrow-pulse etc. In a typical setting this algorithm system provides an error rate of 3/100 at a signal to noise ratio of 0 dB. This algorithm system gives the time frequency detection ratio that may be used to determine if the detected signal falls in Class Single-Carrier of Class Multi-Carrier. Additionally this algorithm system may be used for a number of different applications such as multiple signal identification, finding the basis functions of the received signal and the like.

Abstract: A WRAN discriminates between authentic incumbent and spurious/malicious signals by collaboratively sensing the frequency environment, classifying and fusing the sensed results, and categorizing each signal as valid or invalid. Embodiments categorize signals according to reports from at least two nodes, thereby increasing detection confidence and resisting denial-of-service attacks. A “voting-rule” can be applied whereby a signal is authentic only if it is detected by a specified percentage of the nodes. Some embodiments categorized signals by comparing sensed analog signal properties, such as amplitude, bandwidth, pulse width, mean, variance, modulation, standard deviation, moments, cumulants, and rise and fall times, with properties of known incumbents and/or known incumbent types.

Abstract: Techniques are disclosed that allow for resource allocation during situations requiring co-existence in cognitive radios. Even under situations of bandwidth scarcity, the techniques allow various users to be guaranteed quality of service (QoS) by proper distribution and allocation of resources. The techniques allow wireless communication systems to operate in a normal mode and a co-existence mode. In the co-existence mode of operation, sub-frame creation, sharing and zone formation schemes are implemented that enable the existing underlying frame structure to remain intact and inter-operable with the legacy systems and at the same time, provide a guaranteed QoS. The zones effectively create partitions in space, time and frequency, which result in interference avoidance and allow various users in neighboring cells to communicate on the same frequencies.

Abstract: In a communication system, and in particular a wireless Orthogonal Frequency Division Multiplexing (OFDM) communication system, the present invention provides systems for synchronizing data transmitted across a channel. The present invention may be used in a Multi-Input, Multi-Output (MIMO) system in which the data is transmitted from any number of transmitting antennas and received by any number of receiving antennas. The number of transmitting and receiving antennas does not necessarily have to be the same. Circuitry is provided for synchronizing the data in both the time domain and frequency domain. Time synchronization involves coarse time synchronization and fine time synchronization. Frequency synchronization involves coarse frequency offset estimation, fine frequency offset estimation, and frequency offset correction.

Abstract: A method is disclosed to detect a broad class of signals in Gaussian noise using higher order statistics. The method detects a number of different signal types. The signals may be in the base-band or the pass-band, single-carrier or multi-carrier, frequency hopping or non-hopping, broad-pulse or narrow-pulse etc. In a typical setting this method provides an error rate of 3% at a signal to noise ratio of 0 dB. This method gives the time frequency detection ratio which may be used to determine if the detected signal falls in Class Single-Carrier of Class Multi-Carrier. Additionally, this method may be used for a number of different applications such as multiple signal identification, finding the basis functions of the received signal.

Abstract: Various cognitive communications system architectures and their corresponding Protocol Reference Models (PRMs) are disclosed. Such PRMs incorporate a Cognitive Plane in addition to conventional Data and Management Planes. The additional Cognitive Plane functionality may include, for example, spectrum sensing, spectrum management, geolocation, and security functions. The Cognitive Plane may further include a Policy Engine and a Learning and Reasoning Module. In some embodiments, Management Plane functions may be effectively combined to form a database of primitives (and their respective values) called a Management Information Base (MIB). In addition, techniques are provided by which various components of cognitive and non-cognitive, as well as mesh-enabled and non-mesh-enabled nodes in a network, inter-operate with each other. The architectures allow a Spectrum Manager (or Signal Space Manager) to combine information from various network layers (e.g.

Abstract: Various cognitive communications system architectures and their corresponding Protocol Reference Models (PRMs) are disclosed. Such PRMs incorporate a Cognitive Plane in addition to conventional Data and Management Planes. The additional Cognitive Plane functionality may include, for example, spectrum sensing, spectrum management, geolocation, and security functions. The Cognitive Plane may further include a Policy Engine and a Learning and Reasoning Module. In some embodiments, Management Plane functions may be effectively combined to form a database of primitives (and their respective values) called a Management Information Base (MIB). In addition, techniques are provided by which various components of cognitive and non-cognitive, as well as mesh-enabled and non-mesh-enabled nodes in a network, inter-operate with each other. The architectures allow a Spectrum Manager (or Signal Space Manager) to combine information from various network layers (e.g.

Abstract: A method and system are disclosed to detect a broad class of signals including Advanced Television Systems Committee (ATSC) digital television (DTV) and wireless microphone signals. This signal detection method performs in Gaussian noise, employing Higher Order Statistics (HOS). Signals are processed in time and frequency domains as well as by real and imaginary components. The spectrum sensing employed also supports Denial of Service (DoS) signal classification. The method can include parameters that may be tailored to adjust the probability of detection and false alarm.

Abstract: In a method of cognitive communication for non-interfering transmission, wherein the improvement comprises the step of conducting radio scene analysis to find not just the spectrum holes or White spaces; but also to use the signal classification, machine learning and prediction information to learn more things about the existing signals and its underlying protocols, to find the Gray space, hence utilizing the signal space, consisting of space, time, frequency (spectrum), code and location more efficiently. In a method of cognitive jamming where smart and energy efficient jamming techniques are suggested based on sensing, classification and machine learning of the existing signals.

Abstract: In a communication system, and in particular a wireless Orthogonal Frequency Division Multiplexing (OFDM) communication system, the present invention provides systems for estimating parameters of a channel across which a signal is transmitted. The present invention may be used in a Multi-Input, Multi-Output (MIMO) system in which the data is transmitted from any number of transmitting antennas and received by any number of receiving antennas. The number of transmitting and receiving antennas does not necessarily have to be the same. Circuitry is provided for calculating parameters indicative of the characteristics of the communication channel. Estimates of channel parameters may include channel estimates and noise variance estimates.

Abstract: Apparatus and methods for providing efficient space-time structures for preambles, pilots and data for multi-input, multi-output (MIMO) communications systems are provided. One such embodiment includes providing a computer program that includes logic configured to provide an initial structure. The computer program further includes logic configured to verify that the rows of the initial structure are linearly independent and logic configured to apply an orthonormalization procedure to the initial structure to obtain a space-time structure. Methods are also provided for providing efficient space-time structures for preambles, pilots and data for MIMO communications systems.

Abstract: A communication system is provided herein for transmitting frames across a channel. The frames may be transmitted in single-input, single-output (SISO) and/or multi-input, multi-output (MIMO) communication systems. One such frame includes at least one training symbol, each having a cyclic prefix and a training block. The time length NI of the training block is equal to an integer fraction I of the time length of a data block, i.e., NI=N/I. Furthermore, the time length G of the cyclic prefix is an integer fraction of the time length NI. For example, G may be equal to NI/4 or 25% of NI. The training symbols provide coarse and fine time synchronization, coarse and fine frequency synchronization, channel estimation, and noise variance estimation.

Abstract: In a communication system, and in particular a wireless Orthogonal Frequency Division Multiplexing (OFDM) communication system, the present invention provides systems for synchronizing data transmitted across a channel. The present invention may be used in a Multi-Input, Multi-Output (MIMO) system in which the data is transmitted from any number of transmitting antennas and received by any number of receiving antennas. The number of transmitting and receiving antennas does not necessarily have to be the same. Circuitry is provided for synchronizing the data in both the time domain and frequency domain. Time synchronization involves coarse time synchronization and fine time synchronization. Frequency synchronization involves coarse frequency offset estimation, fine frequency offset estimation, and frequency offset correction.

Abstract: Apparatus and methods for providing efficient space-time structures for preambles, pilots and data for multi-input, multi-output (MIMO) communications systems are provided. One such embodiment includes providing a computer program that includes logic configured to provide an initial structure. The computer program further includes logic configured to verify that the rows of the initial structure are linearly independent and logic configured to apply an orthonormalization procedure to the initial structure to obtain a space-time structure. Methods are also provided for providing efficient space-time structures for preambles, pilots and data for MIMO communications systems.