Method of nonlinear code multiplexing of a multiphase group sequence.

This paper presents the generalization of the method of nonlinear code multiplexing of a binary group sequence is considered for the r – phase group sequences. A transition to a complex space, as well as using definite integrals, and conversion of the Cartesian chart while turning at a set angle are used to form the r – phase group sequence with a constant power from the multiphase summary group sequence, which consist of the sum of the r – phase information orthogonal sequences. As a result, the multiphase summary group sequences are mapped to the r-phase group sequences with constant power, which contain the information orthogonal r-phase sequences which are a part of these summary group sequences. Analytical expressions of the r – phase group sequences with constant power are obtained for even values of r. If the r is 4 the final formulas of group sequences with the constant power at the odd quantity of the information orthogonal sequences in the summary group sequences is obtained. The method of nonlinear code multiplexing of a multiphase group sequence considered in this paper, can be applied to increase capacity of communication channels with nonlinear code multiplexing.

Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences

The number of small sophisticated wireless sensors which share the electromagnetic spectrum is expected to grow rapidly over the next decade and interference between these sensors is anticipated to become a major challenge. In this paper we study the interference mechanisms in one such sensor, automotive radars, where our results are directly applicable to a range of other sensor situations. In particular, we study the impact of radar waveform design and the associated receiver processing on the statistics of radar–radar interference and its effects on sensing performance. We propose a novel interference mitigation approach based on pseudo-random cyclic orthogonal sequences (PRCOS), which enable sensors to rapidly learn the interference environment and avoid using frequency overlapping waveforms, which in turn results in a significant interference mitigation with analytically tractable statistical characterization. The performance of our new approach is benchmarked against the popular random stepped frequency waveform sequences (RSFWS), where both simulation and analytic results show considerable interference reduction. Furthermore, we perform experimental measurements on commercially available automotive radars to verify the proposed model and framework.