Matrix analysis
Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Vector quantization and signal compression
Vector quantization and signal compression
Differential nested lattice encoding for consensus problems
Proceedings of the 6th international conference on Information processing in sensor networks
Communication constraints in the average consensus problem
Automatica (Journal of IFAC)
Distributed Average Consensus using Probabilistic Quantization
SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
The MIMO iterative waterfilling algorithm
IEEE Transactions on Signal Processing
Distributed consensus algorithms in sensor networks: quantized data and random link failures
IEEE Transactions on Signal Processing
The effect of deterministic noise in subgradient methods
Mathematical Programming: Series A and B
IEEE Transactions on Signal Processing
Distributed multiuser power control for digital subscriber lines
IEEE Journal on Selected Areas in Communications
Quantized incremental algorithms for distributed optimization
IEEE Journal on Selected Areas in Communications
A tutorial on decomposition methods for network utility maximization
IEEE Journal on Selected Areas in Communications
Competitive Design of Multiuser MIMO Systems Based on Game Theory: A Unified View
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Signal Processing
| Hi-index | 35.69 |
In this paper, we study the convergence behavior of distributed iterative algorithms with quantized message passing. We first introduce general iterative function evaluation algorithms for solving fixed point problems distributively. We then analyze the convergence of the distributed algorithms, e.g., Jacobi scheme and Gauss-Seidel scheme, under the quantized message passing. Based on the closed-form convergence performance derived, we propose two quantizer designs, namely the Time Invariant Convergence-Optimal Quantizer (TICOQ) and the Time Varying Convergence-Optimal Quantizer (TVCOQ), to minimize the effect of the quantization error on the convergence. We also study the tradeoff between the convergence error and message passing overhead for both TICOQ and TVCOQ. As an example, we apply the TICOQ and TVCOQ designs to the iterative waterfilling algorithm of MIMO interference game.