PHY5 – Coding and energy efficiency
Thursday, 4 June 2026, 16:30-18:00, room Sala 1 (1st floor)
Session Chair: Pawel Kryszkiewicz (Poznan Univ. Technology, PL)
Energy-Efficient Resource Allocation for Joint URLLC and Sensing via SIM
Elaheh Ataeebojd (Center for Wireless Communications, Finland); Mehdi Rasti, Mehdi Monemi and Matti Latva-aho (University of Oulu, Finland)
Stacked intelligent metasurfaces (SIMs) are an emerging reconfigurable hardware architecture that provides additional controllable spatial degrees of freedom via multi-layer programmable metasurfaces. This paper studies an energy efficiency (EE) maximization problem for SIM-enabled joint ultra-reliable low-latency communications (URLLC) and sensing, in which subcarrier allocation, transmit power allocation, and SIM phase shifts are jointly optimized. In this problem, stringent latency and reliability requirements are considered for URLLC users, and target detectability is ensured for sensing targets. The stated problem is a mixed-integer non-convex optimization problem, for which we develop a sub-optimal algorithm. Simulation results demonstrate the effectiveness and performance of the proposed algorithm compared with baseline schemes.
Finite-Alphabet Decoding of LDPC Codes for OFDM-Systems with Higher-Order Modulation
Nicolas Buhr, Tobias Monsees, Dirk Wübben and Armin Dekorsy (University of Bremen, Germany)
Mutual-Information Maximizing Finite-Alphabet (MIM-FA) decoders have been introduced as an approach to reduce the decoding complexity of Low Density Parity Check codes while maintaining performance close to that of Floating-Point (FP) Belief-Propagation (BP) decoders. The applicability of these low-complexity decoders to practically relevant systems with higher-order modulated signals transmitted over multicarrier systems like Orthogonal Frequency Division Multiplexing (OFDM) is crucial for their application in 5G and 6G systems. We propose a pragmatic approach for the design of a receiver structure for a MIM-FA decoders that can deal with the varying reliabilities of OFDM subcarriers and being agnostic to the modulation scheme. The simulation results indicate that the proposed scheme in combination with a 3-bit MIM-FA decoder exploits the full frequency diversity and performs close to FP-BP decoder.
Gearbox PHY for Energy-Efficient Physical Layer: Concept and Demonstration
Ahmad Nimr (Technische Universität Dresden, Germany); Yash Richhariya and Zhitao Lin (Barkhausen Institut, Germany); Abdo Gaber (National Instruments, Germany); Michael Löhning and Vincent Kotzsch (Emerson, Germany); Gerhard P. Fettweis (Technische Universität Dresden, Germany)
Energy efficiency is a fundamental objective for 6G systems and requires adaptive radio operation beyond conventional modulation and coding. While existing approaches rely on duty cycling or component deactivation, substantial savings require hardware-aware adaptability, particularly under low and moderate traffic conditions. This paper investigates a practical Gearbox PHY architecture with a finite set of hardware-aware operating modes (“gears”), each defined by distinct power amplifier (PA) configurations and corresponding achievable SINR ranges. Unlike theoretical designs that assume unconstrained hardware reconfiguration, the proposed approach is compatible with 3GPP NR resource structures and standard signaling. Energy-efficient operation is formulated as a joint optimization of gear selection and discrete time-frequency resource allocation. A real-time testbed based on an OpenAirInterface gNB with dual switchable PAs and synchronized power measurements validates the concept and confirms that multi-gear operation achieves significant energy savings compared to conventional duty cycling using a single transceiver optimized for peak performance.
Proposal for Backward-Compatible 5G NR LDPC Codes
Emmanuelle Bodji (Orange Innovation, France); Emmanuel Boutillon (Université de Bretagne Sud, France); Bruno Jahan (Orange Innovation, France); Christophe Jego (IMS CNRS Laboratory & Bordeaux INP / ENSEIRB-MATMECA, France)
The LDPC codes used in 5th-generation (5G) mobile networks feature an elegant structure that provides flexibility in both code rate and code size, as well as great decoding performance for long code lengths. However, for small code sizes, they suffer from numerous length-4 cycles, which significantly degrade decoding performance. To address this issue, this paper revisits the 5G LDPC base matrix to enhance performance. The proposed approach retains the 5G structure to ensure backward compatibility. It achieves performance gains of up to 0.72 dB in signal-to-noise ratio at a frame error rate of 10−1 with only 5 decoding iterations. The resulting new base matrices exhibit a reduced number of non-zero elements, leading to lower energy consumption.
UPT-Aware Joint Antenna Muting and Micro-DTX for Energy-Efficient Extreme Massive MIMO
Shunsuke Kamiwatari, Takeo Ohseki and Issei Kanno (KDDI Research, Inc., Japan); Silvio Mandelli (Nokia Bell Labs, Germany); Foad Sohrabi (Nokia Bell Labs, USA)
In the development of sixth-generation (6G) networks, extreme massive multiple-input multiple-output (extreme mMIMO) in the FR3 band is expected to provide high-capacity transmission. However, the operational power consumption of hundreds of radio frequency (RF) chains poses a significant sustainability challenge. While conventional energy-saving techniques like antenna muting or micro-discontinuous transmission (micro-DTX) effectively reduce power, they often lead to a trade-off with quality of service (QoS) metrics such as user-perceived throughput (UPT). This paper proposes a hybrid domain adaptation scheme that jointly optimizes spatial-domain muting and time-domain micro-DTX. The proposed algorithm dynamically adjusts the number of active antennas and sleep cycles based on real-time traffic load and UPT-related constraints. System-level simulations using a 3D ray-tracing channel model of a dense urban area demonstrate that our approach achieves superior energy efficiency while maintaining a cell throughput comparable to the baseline. Even under high-traffic scenarios, the proposed method prevents performance degradation by adaptively activating antennas, reconciling the competing demands of energy conservation and high-quality user experience.
