Ordered successive noise projection cancellation algorithm for dual lattice-reduction-aided MIMO detection

A novel nonlinear multi-input multi-output MIMO detection algorithm is proposed which is referred to as an ordered successive noise projection cancellation OSNPC algorithm. It is capable of improving the computation performance of the MIMO detector with the conventional ordered successive interference cancellation OSIC algorithm. In contrast to the OSIC in which the known interferences in the input signal vector are successively cancelled the OSNPC successively cancels the known noise projections from the decision statistic vector. Analysis indicates that the OSNPC is equivalent to the OSIC in error performance but it has significantly less complexity in computation.Furthermore when the OSNPC is applied to the MIMO detection with the preprocessing of dual lattice reduction DLR the computational complexity of the proposed OSNPC-based DLR-aided detector is further reduced due to the avoidance of the inverse of the reduced basis of the dual lattice in computation compared to that of the OSIC-based one. Simulation results validate the theoretical conclusions with regard to both the performance and complexity of the proposed MIMO detection scheme.

STATIONARY OSCILLATIONS OF SECOND ORDER PERIODIC SYSTEMS UNDER STOCHASTIC NOISE INTERFERENCE

In this paper,the existence of stationary oscillations of second order periodic systemsunder stochastlc noise interference is investigated,and the necessary and sufficient condition for the existence of stationary oscillations in the sense of mean-square stability is obtained via establishing equivalent vector stochastic systems and establishing deterministicequivalent systems in the sense of stability, and applying the existence theorem of stationary oscillations for the deterministic systems.

Numerical Implementation of High-Order Vold-Kalman Filter Using Python Arbitrary-Precision Arithmetic Library

The Vold-Kalman(VK)order tracking filter plays a vital role in the order analysis of noise in various fields.However,owing to the limited accuracy of double-precision floating-point data type,the order of the filter cannot be too high.This problem of accuracy makes it impossible for the filter to use a smaller bandwidth,meaning that the extracted order signal has greater noise.In this paper,the Python mpmath arbitrary-precision floating-point arithmetic library is used to implement a high-order VK filter.Based on this library,a filter with arbitrary bandwidth and arbitrary difference order can be implemented whenever necessary.Using the proposed algorithm,a narrower transition band and a flatter passband can be obtained,a good filtering effect can still be obtained when the sampling rate of the speed signal is far lower than that of the measured signal,and it is possible to extract narrowband signals from signals with large bandwidth.Test cases adopted in this paper show that the proposed algorithm has better filtering effect,better frequency selectivity,and stronger anti-interference ability compared with double-precision data type algorithm.