Dr. Julian Renner

Modern wireless communication systems face continuously growing demands for higher data rates. While conventional approaches such as increasing bandwidth or employing higher-order modulation schemes are subject to fundamental limitations, Multiple-Input Multiple-Output (MIMO) technology offers a compelling solution. By exploiting the spatial dimension of the transmission channel, MIMO systems achieve significant gains in data throughput without requiring additional bandwidth or increased transmit power, as the channel capacity of a MIMO channel inherently exceeds that of a Single-Input Single-Output channel. To operate close to this theoretical capacity, transmitted signals are encoded prior to transmission and decoded at the receiver using algorithms that rely on reliability information about the received signals. Log-Likelihood Ratios provide such information, yet their continuous-valued nature makes a floating-point representation bandwidth-inefficient in practice. My research focuses on developing novel quantization strategies that substantially improve bandwidth efficiency while preserving robust decoding performance.

The increasing deployment of connected, cooperative, automated, and autonomous vehicles places simultaneous demands on wireless systems for both reliable high-rate communication and accurate environmental sensing. In the context of Vehicle-to-Everything (V2X) applications — encompassing Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication — dedicated systems for radar sensing and data transmission have traditionally been designed independently, resulting in inefficient use of the available spectrum. Joint Communication and Sensing (JCAS) offers a compelling paradigm to overcome this limitation by enabling a single waveform to serve both purposes concurrently. However, the requirements imposed by high-resolution radar sensing and high-throughput communication are often conflicting, making the co-design of suitable waveforms a non-trivial challenge. My research focuses on the design and analysis of novel waveforms that simultaneously achieve favorable radar sensing characteristics, such as high range and velocity resolution, and support high data rates, thereby advancing the spectral efficiency and practical feasibility of integrated sensing and communication systems for automotive applications.

A sufficiently powerful quantum computer would render several classical public-key cryptosystems insecure, as the underlying mathematical problems — integer factorization and the discrete logarithm problem — can be solved efficiently in a post-quantum setting. In response, the National Institute of Standards and Technology (NIST) initiated the Post-Quantum Cryptography Standardization project to identify and establish quantum-resistant algorithms. My research contributes to this effort by evaluating the hardness of mathematical problems suitable as foundations for post-quantum cryptosystems, analyzing the security of existing schemes, and designing new efficient public-key algorithms. Beyond purely mathematical attacks, my work also addresses the physical security of cryptographic implementations, including side-channel attacks such as power analysis, where an adversary exploits measurable physical characteristics of a device, such as its power consumption, to extract secret information.

Virtually all IP-based traffic in today's communication networks is transmitted over nonlinear optical fiber channels. As future demand scenarios project a continuous increase in required data rates, improving the capacity of optical communication systems has become a critical challenge. Coherent fiber optic telecommunication represents a key enabling technology in this context, as it exploits both the power and the phase of the optical signal, thereby allowing the application of higher-order modulation techniques such as quadrature amplitude modulation. However, uncompensated Kerr nonlinearity fundamentally limits the effective signal-to-noise ratio, preventing straightforward capacity gains through larger modulation alphabets. My research focuses on developing novel methods to increase the spectral efficiency of nonlinear fiber systems, addressing both the theoretical foundations and practical implementation aspects of this challenge.