Optimal and Suboptimal Finger Selection Algorithms for MMSE Rake Receivers in Impulse Radio Ultra-Wideband Systems
Sinan Gezici, Mung Chiang, H. Vincent Poor, Hisashi Kobayashi
Abstract
Convex relaxations of the optimal finger selection algorithm are proposed for a minimum mean square error (MMSE) Rake receiver in an impulse radio ultra-wideband system. First, the optimal finger selection problem is formulated as an integer programming problem with a non-convex objective function. Then, the objective function is approximated by a convex function and the integer programming problem is solved by means of constraint relaxation techniques. The proposed algorithms are suboptimal due to the approximate objective function and the constraint relaxation steps. However, they can be used in conjunction with the conventional finger selection algorithm, which is suboptimal on its own since it ignores the correlation between multipath components, to obtain performances reasonably close to that of the optimal scheme that cannot be implemented in practice due to its complexity. The proposed algorithms leverage convexity of the optimization problem formulations, which is the watershed between `easy' and `difficult' optimization problems.
Create a lesson
Related papers
Optimal Communication for Distributed Sparse Histogram Aggregation
Fangwei Ye, Yijun Fan
Hardware-Efficient Reinforcement-Learned Scheduling for Quantum LDPC Decoders
Mohsen Moradi, Vahid Nourozi, Wei Tang et al.
Making Every Edit Count: Efficient Binary Edit Correction at the Gilbert-Varshamov Bound
Ryan Gabrys, Shubhransh Singhvi, Eitan Yaakobi
Timely Ground-Station Status Delivery via UAV-Assisted Data Collection and Hierarchical RL
Xiangjian Gao, Mohammad Moltafet, Hamid R. Sadjadpour
Uniform Sampling of Linear Codes with Prescribed Hull Dimension
Keita Ishizuka
Quantum Private Information Retrieval on Forests
Mohamed Nomeir, Sennur Ulukus