Abstract
Radio wave propagation can be characterized by two major sets: empirical and deterministic models. Empirical models rely on the received signals’ statistics and thus offer lower precision. Deterministic models have certain physical bases and therefore necessitate a massive amount of geometrical data. For instance, the ray-based technique represents a suitable facility for reliable estimations in indoor schemes. Ultra-wideband (UWB) technology allows transmitting signals over a huge bandwidth, typically in the order of 500 MHz to several GHz enabling the design of communication systems with very high data rates. Massive multiple-input multiple-output (MIMO) is a new technique, utilizing a large number of base station antennas, advancing large system capacities in multiuser schemes, where multiple users are simultaneously served in the same time-frequency resources. We develop a ray-based procedure to investigate the behavior of the downlink UWB massive MIMO channel including the antennas transfer functions under various typical propagation situations. We estimate the magnitude and the phase of the voltage induced at each receiving antenna as a function of frequency (through the reciprocity theorem). We compare the singular value spread (SVS) cumulative distribution function (CDF) of each situation while varying the number of base station antennas. As the number of base station antennas or the inter-user separation increase, both the SVS and the sum-rate improve, the channel becomes more favorable , where better spatial separation is provided, and the disparity of the power values allocated for the users’ channels reduces (through water-filling). The attained monotonic sum-rates were verified with the interference-free sum-rate.
Highlights
Empirical models are used to model radio wave propagation through measurements and statistics
Based on geometrical optics (GO) and the uniform theory of diffraction (UTD), the ray-based approach is well suited for the study of radio wave propagation since it speeds up complex calculations, offers simplifications in the physical processes used, and keeps a reasonable precision [3]–[11]
Through the water-filling algorithm to optimally allocate the total transmitted power over the users’ channels to attain maximum mutual information over the massive multiple-input multiple-output (MIMO) channel, which agrees with the power allocated for each user channel while achieving the massive MIMO channel sum-rate capacity through the dirty-paper coding (DPC) scheme, the results show that as the number of base station antennas increases, the disparity of the power values allocated for the users’ channels significantly decreases
Summary
Empirical models are used to model radio wave propagation through measurements and statistics. They are fast and easier to build but are less sensitive to the environmental geometry and cause relatively inferior precision [1], [2]. Deterministic models rely on physical laws and require the availability of a huge amount of data regarding geometry and locations of buildings. Based on geometrical optics (GO) and the uniform theory of diffraction (UTD), the ray-based approach is well suited for the study of radio wave propagation since it speeds up complex calculations, offers simplifications in the physical processes used, and keeps a reasonable precision [3]–[11]. The associate editor coordinating the review of this manuscript and approving it for publication was Yi Fang .
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