This work presents a simulation architecture to validate Advanced Driver Assistance Systems (ADAS). The realization of secure autonomous vehicles is closely connected to the possibility of validating the functionality of ADAS. The high-dimensional parameter range of simulation scenarios, including for example weather conditions, traffic flow or material properties, enforces to shift tests from reality to computer based simulations. To enable tests of physical prototypes in an early stage of development, these devices have to be included in the simulation. An approach how to combine various simulation domains and perform ADAS relevant simulations is presented.

The transmission over the Gaussian mixture noise channel with perfect channel state information at the receiver side is considered. Lower and upper bounds on the achievable pairwise error probability (PEP) are derived for finite and infinite codeword lengths. It is shown that diversity codes, i.e., unitary transforms, can be applied to achieve a diversity gain. A large class of diversity codes is determined for which-if the codeword length is increased-the PEP between any two codewords approaches either zero or the lower bound on the PEP.

We discuss the decoding of error-correcting block codes over complex numbers for the transmission over impulsive noise channels. The encoder multiplies a vector of complex information symbols resulting from a modulation scheme, e.g., quadrature amplitude modulation (QAM), with a unitary generator matrix G. Choosing the inverse Fourier transform as G, the encoding procedure is similar to orthogonal frequency-division multiplex (OFDM) modulation. The maximum a posteriori (MAP) receiver is analyzed and a suboptimum decoder based on the turbo decoding principle is derived. Simulation results show the excellent performance of the iterative decoder.

The transmission over the memoryless additive white Class-A noise (AWCN) channel is considered. For uncoded transmission, an exact expression for the symbol error rate is derived. For coded transmission, the Chernoff bound on the pairwise error probability is calculated and the performance achieved on the real and the complex AWCN channels is compared. Moreover, a low-complexity, suboptimum decoding metric is derived and analyzed employing the cutoff rate as a performance criterion.