Abstract
The simulation of electromagnetic wave propagation in time-variant wideband multiple-input multiple-output mobile radio channels using a geometry-based channel model (GCM) is computationally expensive. Due to multipath propagation, a large number of complex exponentials must be evaluated and summed up. We present a low-complexity algorithm for the implementation of a GCM on a hardware channel simulator. Our algorithm takes advantage of the limited numerical precision of the channel simulator by using a truncated subspace representation of the channel transfer function based on multidimensional discrete prolate spheroidal (DPS) sequences. The DPS subspace representation offers two advantages. Firstly, only a small subspace dimension is required to achieve the numerical accuracy of the hardware channel simulator. Secondly, the computational complexity of the subspace representation is independent of the number of multipath components (MPCs). Moreover, we present an algorithm for the projection of each MPC onto the DPS subspace in operations. Thus the computational complexity of the DPS subspace algorithm compared to a conventional implementation is reduced by more than one order of magnitude on a hardware channel simulator with 14-bit precision.
Highlights
In mobile radio channels, electromagnetic waves propagate from the transmitter to the receiver via multiple paths
It can be seen that the complexity of the approximate discrete prolate spheroidal (DPS) subspace representation in terms of number of arithmetic operations as well as memory access operations increases with slope D, while the complexity of the sum of complex exponentials (SoCE) algorithm increases with slope M
The more multipath components (MPCs) are used in the geometry-based channel model (GCM), the more complexity is saved
Summary
Electromagnetic waves propagate from the transmitter to the receiver via multiple paths. The processing power of the baseband unit limits the number of MPCs that can be calculated and the model accuracy. On the ARC SmartSim channel simulator [2], for example, the baseband processing hardware uses 16-bit fixedpoint processors and an analog/digital converter with 14-bit precision This corresponds to a maximum achievable accuracy of Emax = 2−13. Using multidimensional DPS sequences, the DPS subspace representation can be extended to simulate time-variant wideband MIMO channel models. Our new approach presented in this paper allows us to reduce the complexity of Clarke’s original model by more than an order of magnitude without imposing any restrictions on the AoAs. Contributions of the paper (i) We apply the DPS subspace representation to derive a low-complexity algorithm for the computation of the GCM.
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