64 results about "Maximum likelihood detector" patented technology

A MIMO receiver is provided with a preprocessor for performing QR decomposition of a channel matrix H wherein the factored reduced matrix R is used in place of H and Q*y is used in place of the received vector y in a maximum likelihood detector (“MLD”). The maximum likelihood detector might be a hard-decision MLD or a soft-decision MLD. A savings of computational complexity can be used to provide comparable results more quickly, using less circuitry, and/or requiring less consumed energy, or performance can be improved for a fixed amount of time, circuitry and/or energy. Where the MLD uses approximations, such as finite resolution calculations (fixed point or the like) or L1 Norm approximations, the reduced number of operations resulting from using the reduced matrix results in improved approximations as a result of the finite resolution operations. Other methods of reducing the channel matrix might be used for suitable and/or cumulative advantages.

By embedding as a Physical Layer (PHY) Appliqué patterns (time, frequency, tone multiplexed, control signal, explicit network authentication, projective, other, or combined) on wireless electronic communications network (WECN) digital signal packets, and using a QRD-based auto-SCORE adaptation algorithm to maximize the signal-to-interference-and-noise ratio (SINR) attainable by multielement arrays over very small time-bandwidth products, differentiation and detection of signals from environmental noise (particularly from other or non-network signals) can be improved, allowing more compressed, secure, efficient network operations. By projecting the signal embedding onto a known linear subspace and using integrated transmit/receive structures, packet detection algorithms, and blind array adaptation algorithms, the WECN processes the data received with constant false-alarm rate, generalized, maximum-likelihood detectors and multilink signal estimation algorithms, based only on knowledge of the embedding pattern used at the transmit node. The resultant system provides PHY information-assured (PHY-IA) data transmission with improved network efficiency and security.

A receiver uses a transmission channel matrix to obtain a superior signal separation characteristic regardless of differences in levels of multipath signals. A multipath linear combining unit performs linear combining of the multipaths in received signals of the reception antennas by means of the transmission channel matrix between the plurality of transmission antennas and the plurality of reception antennas. A maximum likelihood detector compares signals in which multipaths have been combined by the multipath linear combining unit with reception replicas that have been found using the transmission channel matrix to estimate the transmitted signals of each of the transmission antennas.

The invention discloses a system and a method for realizing iterative timing synchronization of a continuous phase modulation (CMP) signal; the system is provided with a sender, and is composed of a maximum likelihood detector, a de-interleaver, a channel decoder and an information destination which are connected in order, and an interleaver which is used for interleaving an output signal of the channel decoder and feeding back the interleaved output signal to the maximum likelihood detector; a built-up circuit of the maximum likelihood detector comprises a match filter set, a demodulator, and a timing synchronization loop circuit arranged between the match filter set and the demodulator; a detecting method based on a maximum likelihood criterion is used for demodulating the received CPM signal, detecting and computing a timing error value and adjusting the time delay, and outputting a bit likelihood ratio of each symbol. Based on a timing error detecting method of the maximum likelihood criterion, a soft information assistance fed back by the channel decoder is used for realizing the timing synchronization to obtain an accurate timing deviation estimation; meanwhile, an iterativeprocess is used between the demodulation and the decoding to maximally improve an error bit ratio of the system; and the system and method for realizing iterative timing synchronization of the CMP signal can be applied in long-distance communication with the requirement of high performance.

The invention discloses a cooperative frequency spectrum sensing method for a cognitive radio network. The method comprises the following steps that: (1) the cognitive radio network which comprises N cognitive users SU and an information fusion center FC is configured in a network with an existing privileged user PU; (2) the cognitive user SU uses energy detection to independently judge whether aprivileged user PU signal is present, and transmits a binary hard decision result to the information fusion center FC, and the transmitting power of the cognitive user is adaptively adjusted according to the condition of a channel from the privileged user PU to the cognitive user SU; and (3) the information fusion center FC fuses the results of a plurality of cognitive users SU by adopting a maximum likelihood detector, and finally determines whether the privileged user PU is occupying the frequency spectrum. The cognitive user SU can independently process the signal without transmitting softinformation or interchanging information; and a detector in the information fusion center FC has a simple structure and is easy to implement. Meanwhile, the cooperative frequency spectrum sensing method has good performance such as low communication overhead, high diversity gain, low false alarm rate and lost detection rate and the like, and has high practical value.

A reduced-complexity maximum-likelihood detector that provides a high degree of signal detection accuracy while maintaining high processing speeds. A communication system implementing the present invention comprises a plurality of transmit sources operable to transmit a plurality of symbols over a plurality of channels, wherein the detector is operable to receive symbols corresponding to the transmitted symbols. The detector processes the received symbols to obtain initial estimates of the transmitted symbols and then uses the initial estimates to generate a plurality of reduced search sets. The reduced search sets are then used to generate decisions for detecting the transmitted symbols. In various embodiments of the invention, the decisions for detecting the symbols can be hard decisions or soft decisions. Furthermore, in various embodiments of the invention, the initial estimates can be obtained using a plurality of linear equalization techniques, including zero-forcing equalization, minimum-mean-squared-error equalization. The initial estimate can also be obtained by nulling and canceling techniques. In various embodiments of the invention, the data output corresponding to the transmitted symbols can be obtained using a log-likelihood probability ratio. The method and apparatus of the present invention can be applied to any communication system with multiple transmit streams.

A disk evaluating device includes a PR equalizer that equalizes reproduced signals from a disk to a response waveform of a partial response of a predetermined class, a maximum likelihood detector that performs maximum likelihood decoding on output signals from the PR equalizer, and an evaluating unit that classifies binary data output from the maximum likelihood detector into bit patterns of strings of consecutive bits, each of the strings having a predetermined length, and obtaines a histogram of amplitudes of the output signals from the PR equalizer for each of the bit patterns.

A FOW-based 2-by-2 space-time MIMO wireless system based on Alamouti's Space-Time block code with a feedback optimum weight (FOW) technique is provided, including a MIMO transmitter, a 2-by-2 MIMO channel, two FOW-based MIMO receivers, an optimum weight vector module, a Bayes decision algorithm module, a coherent combining unit, and a maximum likelihood detector (MLD). The FOW-based 2-by-2 space-time MIMO wireless system of the present invention uses the Bayes decision algorithm to determine the optimum weights at the receiver which multiplies the transmitted output signals at spatial antennas via up-link Fast Channel Feedback (i.e. closed-loop MIMO) and also the corresponding receiving signals. In addition, the present invention includes a Scheduler design to arrange these weight elements in accordance with space-time constellation signals, which allows linear processing using Alamouti's 2-branch maximum likelihood detection without increasing the hardware complexity.

A method and apparatus is provided for determining a modulation and coding scheme in a Multiple Input Multiple Output system with a Maximum Likelihood Detector (MIMO-MLD), in which an upper bound and a lower bound of a Signal to Noise Ratio (SNR) for the MIMO-MLD are determined, an effective Signal to Noise Ratio (eSNR) is computed using a relation between the upper bound and the lower bound, a channel quality is estimated using the eSNR, and a modulation and coding scheme is determined using the estimated channel quality.

A maximum likelihood decoder creates a decoding target data string and provides error candidates that are effective for an error correction circuit. The decoder has a detector for creating a decoding target data string, and an error candidate extractor for extracting the bit positions of which likelihood of each bit shows a high probability of error as the error candidates of the decoding target data string based on the likelihood information from the detector. Since only the bit positions of which error probability is high are extracted as error candidates, a correction circuit can extract the error candidates in the sequence of the lower likelihood, and the number of times of sorting in the sequence of likelihood can be decreased.

A data recovery system and method is disclosed. Said data recovery system comprises a maximum-likelihood detector, a non-maximum likelihood detector, a decision unit, and a selecting unit. The maximum-likelihood detector transforms a digital signal into a first binary signal. The non-maximum likelihood detector transforms the digital signal into a second binary signal. The decision unit detects a difference between the first binary signal and the second binary signal, and outputs a selecting signal based on the difference. The selecting unit coupled to the maximum-likelihood detector, the non-maximum likelihood detector, and the decision unit selectively outputs the first binary signal or the second binary signal based on the selecting signal.

The present invention relates to communication technology. The present invention solves the disadvantage that the detection complexity is too high to be implemented when there are many transmission signal paths in the existing combined input signal MIMO wireless communication system, and provides a combined input signal MIMO wireless communication receiving end and a signal detection method thereof , the technical solution can be summarized as follows: combined input signal MIMO wireless communication receiving end, its reference signal input end is connected to the system state information processing module, multiple receiving antennas are connected to the linear detection module, and the linear detection module is connected to each maximum likelihood detection module respectively. The modules are connected, each maximum likelihood detection module is connected to each corresponding system output terminal, and the system state information processing module is respectively connected to each maximum likelihood detection module, linear detection module and each system output terminal. The beneficial effect of the present invention is that the complexity is relatively low, and it is suitable for combining input signal MIMO wireless communication systems.

An improved multi-antenna receiver is realized for detecting signals transmitted by a multi-antenna transmitter by summing signals received at the plurality of receiver antennas after multiplying each by a respective constant. The summed signal is applied to a maximum likelihood detector. The respective constants, λ_j, where j is an index designating a particular receiver antenna, are determined by evaluating the largest eigenvector of the matrix A, where Λ is a vector containing the values λ_j, and A is a matrix containing elements α_ij, which is the transfer function between the i^th transmitter antenna to the j^th receiver antenna. The α_ij terms are determined in the receiver in conventional ways.

The present invention provides a multiple-aerial system transmitting system and a modulation mode selecting method of the non-ideal communication channel. In the Rayleigh channel mode the receiver is provided with ideal communication channel information and adopts the maximum likelihood detector for respectively simulating in different modulation modes to obtain the system error code ratio curve. According to the request of the system error code ratio, the ideal signal-to-noise ratio threshold of the complexing system and the diversity system satisfying the request of the error code ratio is obtained. Afterwards in the actual communication system, the non-ideal signal-to-noise threshold is obtained with the mean square error between the signal-to-noise ratio threshold and the non-ideal communication channel information, and the non-ideal signal-to-noise ratio is compared with the signal-to-noise of current system. Then a transmitting mode and modulating mode which satisfy the request of the error code ratio and have maximum frequency spectrum efficiency are selected for feedbacking to the transmitting side. The transmitter adjusts the current transmitting mode and modulating mode according to the feedback information. The invention can correctly select the transmitting mode and modulating mode according to the system environment and the mean square error of the non-ideal communication channel information and evidently increase the frequency spectrum efficiency of the system.

The invention relates to the technology of communications, solves the defect that existing LRA-OSIC detector still has a big gap with the performance of a maximum likelihood detector when there are alarge number of antennas, and provides an MIMO detection method based on model disturbance and lattice reduction. The technical solution thereof may be summarized as: the method generates a pluralityof disturbance models of the same MIMO channel, constructs a standard LRA-OSIC detector for each model then, selects an optimal detector by using a maximum-likelihood criterion, and combines the stopping criterion to reduce the complexity. The invention has the beneficial effect that the bit error rate is obviously reduced only by increasing the complexity moderately.

The invention discloses a method and a device for estimating carrier to interference noise ratio (CINR) of a maximum likelihood detector (MLD) receiver in a multiple input multiple output (MIMO) system. The method comprises the following steps of: for each transmitting signal, acquiring wireless channel response of the transmitting signal to a plurality of receiving antennas and covariance of noise and interference, wherein the interference covariance is the sum of wireless channel united response of other transmitting signals; and for each transmitting signal, calculating the CINR of the transmitting signal according to the wireless channel response and the covariance of noise and interference. The device comprises a channel response acquisition module, a covariance acquisition module and a CINR calculation module for calculating the CINR of the transmitting signal according to the wireless channel response and the covariance of noise and interference for each transmitting signal. The method and the device implement CINR estimation of the MLD receiver, and also can estimate multiple users.

The invention discloses a generalized dimming control method based on a multi-LED visible light communication system, and belongs to the field of wireless communication. The generalized dimming control method includes the steps: firstly, constructing a hybrid dimming module is constructed, initializing the number of space-time matrix activation elements, converting source bit information into a plurality of data blocks in a serial-parallel mode, mapping each data block into a space-time matrix, and transmitting the information through a visible light communication channel with the space-time matrix as a unit; calculating a direct current gain of the user channel matrix, and detecting and demodulating an electric signal receiving matrix obtained by conversion of the optical detector througha maximum likelihood detector; and calculating a joint boundary of corresponding system bit error rates when different numbers of elements are activated in the space-time matrix, and determining an optimal value of the number of the activation elements of the space-time matrix by taking the minimum bit error rate of the system as an optimization target and taking the dimming level and the spectral efficiency as constraint conditions. The generalized dimming control method effectively considers communication and lighting functions of the visible light communication system, can effectively improve the energy efficiency of the system, and can enhance the bit error rate performance of the system.

The invention relates to a dual-mode orthogonal frequency division multiplexing index modulation detection method and device based on deep learning. The dual-mode orthogonal frequency division multiplexing index modulation detection method comprises the following steps: (1) data preprocessing: preprocessing an obtained DMOFDMIM signal and an obtained channel; (2) training a DMOFDMIM model: takingthe preprocessed data obtained in the step (1) as the input of the DMOFDMIM model, and carrying out the offline training of the DMOFDMIM model; and (3) on-line modulation: carrying out on-line modulation on the new DM-OFDM-IM signal under the Rayleigh channel condition through the trained DM-OFDM-IM model. According to the detection and demodulation scheme based on the deep neural network providedby the invention, the bit error rate close to the maximum likelihood detector can be achieved in a relatively short operation time.

The present invention relates to a maximum likelihood detector and a maximum likelihood detection method. The maximum likelihood detector a comprises a searching value selection circuit; and a maximum likelihood detection circuit. The searching value selection circuit is configured to decide the first layer of searching values. The maximum likelihood detection circuit is configured to execute the following steps: selecting the first layer of candidate signal values according to a receiving signal or a derivative signal thereof, a channel estimation signals or a derivative signal thereof and the first layer of the searching values, and supplementing one or more than one candidate signal values as required; calculating the second layer of the candidate signal values according to the first layer of the candidate signal values, and supplementing one or more than one candidate signal values and corresponding first layer of the candidate signal values as required; and calculating the log-likelihood ratio according to all the first layer of the candidate signal values and the second layer of the candidate signal values.

A transmitter codes data to be transferred, performs serial-parallel conversion of the data to two signal groups, and passes one of the groups to a first transmission unit and the other one to a second transmission unit. Each of the first transmission unit and the second transmission unit performs a prephasing process on each of signals included in the input signal group received, performs inverse Fourier transform thereon, and transmits the signal with a predetermined polarization. The polarity of the predetermined polarization of the first transmission is orthogonal to a polarity of the predetermined polarization of the second transmission unit. A receiver receives a signal transmitted from the transmitter with a predetermined polarization, performs Fourier transform thereon, performs MLD (Maximum Likelihood Detector) detection thereof, performs parallel-serial conversion in a parallel-serial converting unit, and decodes a signal originating from the parallel-serial conversion to output the transferred signal. The transmitter performs the prephasing process on each of the signals based on feedback information sent from the receiver in such a way that a probability that a same phase is generated becomes lower.