An Additive Noise Modeling Technique for Accurate Statistical Study of Residual RF Hardware Impairments

Abstract

Hardware impairments are the inevitable limiting factors in radio frequency communication systems, and in particular in mm-wave, the impairments can severely affect system performance. In this paper, we propose an additive noise modeling technique for modeling and analyzing the residual hardware impairments, more accurately than previously done in the literature. We analyze the effects of joint residual phase noise and IQI in both transmitter and receiver by using additive noise modeling as a representation method and indicate how other impairments can be described in the same framework. We derive the signal to distortion plus noise ratio (SDNR) for both the joint and the individual effects of impairments and validate the formulations with simulations which also acknowledge the usefulness of the additive noise modeling as a mean for accurate hardware impairments study. Index Terms-Hardware impairments, residual phase noise, IQI, additive noise modeling, variance of error.

Statistical Study of Hardware Impairments Effect on mmWave 77 GHz FMCW Automotive Radar

“…Ae j∆ϕ(t) βz(t) +ω(t) + Aαe −j∆ϕ(t) β * z * (t) + αω * (t). (11) By considering ∆ϕ(t) small enough, we can approximate the exponential of ∆ϕ(t) with its Taylor expansion and rewrite (11) as [2] y B (t)≈…”

“…To collect all the parameters in a single metric and track them more easily, we can use signal to distortion plus noise ratio (SDNR) [2]…”

“…where Y HI [p, q, θ, ϕ] is the digital video signal considering hardware impairments, andσ 2 Λ andσ 2 Π are the estimated desired and distortion powers. The threshold T (σ 2 Λ ,σ 2 Π ) is a function ofσ 2 Λ andσ 2 Π which should be determined based on the hardware impairment parameter estimations which by now is out of the scope of this paper and is left to be done in an extension of this paper in future.…”

“…The first step in handling the destructive effects of hardware impairments is to analyze them with the aid of accurate models. Evaluating the performance in terms of impairment parameters and residual effects is studied extensively in both communication [2]- [5] and radar [6]- [12] literature within several different settings. Phase noise, IQI, and oscillator spurs are the most severe hardware impairments in the FMCW radar systems [6], [12].…”

“…In this paper, we will use additive noise modeling introduced in [2], to analyze the joint effect of IQI and phase noise in mmWave FMCW automotive radar. Following the cost-performance trade-off in the mass-production of automotive radar sensors, system designers need to have accurate measures for optimizing the design in the production chain, and for doing so, they need to know the contribution of each hardware impairment effect on the system performance and the resulting cost for compensation in detailed scales.…”