174 research outputs found

    Optimal Signaling of MISO Full-Duplex Two-Way Wireless Channel

    Full text link
    We model the self-interference in a multiple input single output (MISO) full-duplex two-way channel and evaluate the achievable rate region. We formulate the boundary of the achievable rate region termed as the Pareto boundary by a family of coupled, non-convex optimization problems. Our main contribution is decoupling and reformulating the original non-convex optimization problems to a family of convex semidefinite programming problems. For a MISO full-duplex two-way channel, we prove that beamforming is an optimal transmission strategy which can achieve any point on the Pareto boundary. Furthermore, we present a closed-form expression for the optimal beamforming weights. In our numerical examples we quantify gains in the achievable rates of the proposed beamforming over the zero-forcing beamforming.Comment: To appear in IEEE ICC 2015, London, U

    Fast Multi-user Detector for a Time-varying CDMA System

    Get PDF
    This paper investigates methods to reduce the amount of computation needed to detect information bits using a linear detector for a CDMA system. We show windowing technique coupled with pipelining can reduce the amount of computation without significantly sacrificing the performance of linear feedback detector. We also describe efficient techniques to adapt to a dynamic system where the system parameters vary due to the change in delays associated with individual users.Nokia CorporationNational Science FoundationTexas Advanced Technology Progra

    Low Complexity Iterative Multiuser Detection and Decoding for Real-Time Applications

    Get PDF
    This paper presents a low-complexity multiuser decoding technique that can be implemented in real time for a convolutionally coded direct sequence code division multiple access (DS-CDMA) system. The main contribution, denoted here as the iterative prior update (IPU), consists of iterative interference cancellation and prior updates on sequences of coded bits combined with M-algorithm and list decoding. We illustrate performance gains over other low-complexity sequence detection and decoding strategies and argue that the algorithm converges within a few iterations and requires only a small size buffer for keeping track of the priors along iterations. The fact that the we can use existing available architectures for Viterbi decoding with slight modifications and can meet the real-time processing constraints makes the IPU algorithm an attractive alternative for cellular systems

    Mutual Information in Frequency and its Application to Measure Cross-Frequency Coupling in Epilepsy

    Full text link
    We define a metric, mutual information in frequency (MI-in-frequency), to detect and quantify the statistical dependence between different frequency components in the data, referred to as cross-frequency coupling and apply it to electrophysiological recordings from the brain to infer cross-frequency coupling. The current metrics used to quantify the cross-frequency coupling in neuroscience cannot detect if two frequency components in non-Gaussian brain recordings are statistically independent or not. Our MI-in-frequency metric, based on Shannon's mutual information between the Cramer's representation of stochastic processes, overcomes this shortcoming and can detect statistical dependence in frequency between non-Gaussian signals. We then describe two data-driven estimators of MI-in-frequency: one based on kernel density estimation and the other based on the nearest neighbor algorithm and validate their performance on simulated data. We then use MI-in-frequency to estimate mutual information between two data streams that are dependent across time, without making any parametric model assumptions. Finally, we use the MI-in- frequency metric to investigate the cross-frequency coupling in seizure onset zone from electrocorticographic recordings during seizures. The inferred cross-frequency coupling characteristics are essential to optimize the spatial and spectral parameters of electrical stimulation based treatments of epilepsy.Comment: This paper is accepted for publication in IEEE Transactions on Signal Processing and contains 15 pages, 9 figures and 1 tabl

    Maximum Likelihood Multipath Channel Parameter Estimation in CDMA Systems

    Get PDF
    The problem addressed in this paper is the estimation of the channel parameters in a Code Division Multiple Access(CDMA) communication system, in the presence of multipath effects. Maximum likelihood estimation of these parameters has been investigated in the past with the main drawback being the complexity of the multi-dimensional algorithms. The algorithm presented in this paper elegantly decomposes the multiuser problem into a series of single user problems. The algorithm first estimates a composite channel impulse response of each user and then extracts the channel parameters of all the paths of each user from the channel impulse response. We evaluate the performance of the algorithm through simulation studies