Multicell Coordinated Beamforming with Rate Outage Constraint--Part I: Complexity Analysis

This paper studies the coordinated beamforming (CoBF) design in the multiple-input single-output interference channel, assuming only channel distribution information given a priori at the transmitters. The CoBF design is formulated as an optimization problem that maximizes a predefined system utility, e.g., the weighted sum rate or the weighted max-min-fairness (MMF) rate, subject to constraints on the individual probability of rate outage and power budget. While the problem is non-convex and appears difficult to handle due to the intricate outage probability constraints, so far it is still unknown if this outage constrained problem is computationally tractable. To answer this, we conduct computational complexity analysis of the outage constrained CoBF problem. Specifically, we show that the outage constrained CoBF problem with the weighted sum rate utility is intrinsically difficult, i.e., NP-hard. Moreover, the outage constrained CoBF problem with the weighted MMF rate utility is also NP-hard except the case when all the transmitters are equipped with single antenna. The presented analysis results confirm that efficient approximation methods are indispensable to the outage constrained CoBF problem.Comment: submitted to IEEE Transactions on Signal Processin

A new iterative WLS Chebyshev approximation method for the design of two-dimensional FIR digital filters

[[abstract]]In this paper, based on Chi-Chiou's weighted least-squares (WLS) Chebyshev approximation method which is for the design of one-dimensional (1-D) FIR digital filters with arbitrary complex frequency response, we propose a new iterative WLS Chebyshev approximation method for the design of two-dimensional (2-D) FIR digital filters with arbitrary complex frequency response. Several design examples are provided to justify the good performance of the proposed approximation method.[[fileno]]2030157030004[[department]]電機工程學

An adaptive Bernoulli-Gaussian model based maximum-likelihood channel equalizer for detection of binary sequences

[[abstract]]Based on a modified Bernoulli-Gaussian model, we propose an adaptive maximum-likelihood channel equalizer, which is a block signal processing algorithm, for the detection of binary sequences transmitted through an unknown slowly time-varying channel. Both computational load and storage required by the proposed adaptive channel equalizer are linearly rather than exponentially proportional to the size of signal processing block. A simulation example is provided to support that it can simultaneously track the variation of slowly time-varying channels and detect unknown binary sequences well.[[fileno]]2030157030002[[department]]電機工程學