Channel Sparsity Variation and Model-Based Analysis on 6, 26, and 105 GHz Measurements
Ximan Liua, Jianhua Zhanga, Pan Tanga, Lei Tiana, Harsh Tatariab, Shu Dong Sunc d, Mansoor Shafie
- aState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China
- bTataria Consulting, Wellington, New Zealand
- cDepartment of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China
- dDepartment of Electronic Engineering and the Cooperative Medianet Innovation Center (CMIC), Shanghai Jiao Tong University, Shanghai, China
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Abstract
Triggered by the introduction of higher frequencies (above 24 GHz), there has been a long-standing debate in the radio propagation community on whether higher frequency radio channels are sparser relative to channels below 6 GHz. Here, sparsity implies a few dominant multipath components containing the vast majority of the electromagnetic energy. This discussion has recently been revisited with the study and interest in bands above 100 GHz for future wireless access. In this paper, the level of sparsity is examined at 6, 26, and 105 GHz carrier frequencies by conducting channel measurements in an indoor office environment. By using the Gini index (value between 0 and 1) as a metric for characterizing sparsity, we show that increasing carrier frequency leads to increased levels of sparsity. The measured channel impulse responses are used to derive a Third-Generation Partnership Project (3GPP)-style propagation model, used to calculate the Gini index for the comparison of the channel sparsity between the measurement and simulation based on the 3GPP model. Our results show that the mean value of the Gini index in measurement is nearly twice the value in simulation, implying that the 3GPP channel model does not capture the effects of sparsity in the delay domain as frequency increases. In addition, a new intra-cluster power allocation model based on measurements is proposed to characterize the effects of sparsity in the delay domain of the 3GPP channel model. The accuracy of the proposed model is analyzed using theoretical derivations and simulations. Using the derived intra-cluster power allocation model, the mean value of the Gini index is 0.91 in the sub-THz band, while the spread of variability is restricted to 0.01, demonstrating that the proposed model is suitable for 3GPP-type channels. To our best knowledge, this paper is the first to perform measurements and analysis across a wide range of frequencies for the evaluation of channel sparsity in the same environment.