A Constrained Adaptive Active Noise Control Filter Design Method Via Online Convex Optimization

In practical active noise control (ANC) applications, various types of constraints may need to be satisfied, e.g., robust stability, disturbance enhancement, and filter output power constraint. Some adaptive filters such as leaky LMS have been developed to apply required constraints indirectly. However, when multiple constraints are required simultaneously, satisfactory noise performance is difficult to achieve by tuning only one leaky factor. Another filter design approach that may achieve better noise control performance is to solve a constrained optimization problem. But the computational complexity of solving such a constrained optimization problem for ANC applications is usually too high even for offline design. Recently, a convex optimization reformulation is proposed which significantly reduces the required computational effort in solving constrained optimization problems for active noise control applications. In the current work, a constrained adaptive ANC filter design method is proposed. The previously proposed convex formulation is improved so that it can be implemented in real-time. The optimal filter coefficients are then redesigned continuously using online convex optimization when the environment is time-varying

MIMO Radar Waveform Optimization With Prior Information of the Extended Target and Clutter

The concept of multiple-input multiple-output (MIMO) radar allows each transmitting antenna element to transmit an arbitrary waveform. This provides extra degrees of freedom compared to the traditional transmit beamforming approach. It has been shown in the recent literature that MIMO radar systems have many advantages. In this paper, we consider the joint optimization of waveforms and receiving filters in the MIMO radar for the case of extended target in clutter. A novel iterative algorithm is proposed to optimize the waveforms and receiving filters such that the detection performance can be maximized. The corresponding iterative algorithms are also developed for the case where only the statistics or the uncertainty set of the target impulse response is available. These algorithms guarantee that the SINR performance improves in each iteration step. Numerical results show that the proposed methods have better SINR performance than existing design methods

Mirror Prox Algorithm for Large-Scale Cell-Free Massive MIMO Uplink Power Control

We consider the problem of max-min fairness for uplink cell-free massive multiple-input multiple-output (MIMO) subject to per-user power constraints. The standard framework for solving the considered problem is to separately solve two subproblems: the receiver filter coefficient design and the power control problem. While the former has a closed-form solution, the latter has been solved using either second-order methods of high computational complexity or a first-order method that provides an approximate solution. To deal with these drawbacks of the existing methods, we propose a mirror prox based method for the power control problem by equivalently reformulating it as a convex-concave problem and applying the mirror prox algorithm to find a saddle point. The simulation results establish the optimality of the proposed solution and demonstrate that it is more efficient than the known methods. We also conclude that for large-scale cell-free massive MIMO, joint optimization of linear receive combining and power control provides significantly better user fairness than the power control only scheme in which receiver coefficients are fixed to unity.Comment: in IEEE Communications Letters, 202

Efficient algorithm for solving semi-infinite programming problems and their applications to nonuniform filter bank designs

An efficient algorithm for solving semi-infinite programming problems is proposed in this paper. The index set is constructed by adding only one of the most violated points in a refined set of grid points. By applying this algorithm for solving the optimum nonuniform symmetric/antisymmetric linear phase finite-impulse-response (FIR) filter bank design problems, the time required to obtain a globally optimal solution is much reduced compared with that of the previous proposed algorith