Low latency and high data rate performance are essential in wireless communication systems. This paper explores trade-offs between latency and data rates for optical wireless communication. We introduce a latency-optimized model utilizing compound codes as one corner case and a data rate-optimized model employing channel estimation via pilot signals and feedback before data transmission. Trade-offs between the two extremes are displayed. Most importantly, we detail operating points that can only be reached when the receiver side of the link employs optimal quantum measurement strategies. Furthermore, we propose an IoT application in a robot factory as an example scenario. Our findings reveal a trade-off between latency and data rate driven by two basic algorithms: compound codes reduce latency at the cost of data rates, while channel estimation enhances data rates at the cost of latency.
Low latency and high data rate performance are essential in wireless communication systems. This paper explores trade-offs between latency and data rates for optical wireless communication. We introduce a latency-optimized model utilizing compound codes as one corner case and a data rate-optimized model employing channel estimation via pilot signals and feedback before data transmission. Trade-offs between the two extremes are displayed. Most importantly, we detail operating points that can only be reached when the receiver side of the link employs optimal quantum measurement strategies. Furthermore, we propose an IoT application in a robot factory as an example scenario. Our findings reveal a trade-off between latency and data rate driven by two basic algorithms: compound codes reduce latency at the cost of data rates, while channel estimation enhances data rates at the cost of latency.
Recent efforts in the design of communication systems have in addition to data rates embraced a focus on other metrics, such as round-trip latency. Data transmission over a channel is typically preceded by so-called pilot symbols, which let the receiver learn the channel conditions. Together with appropriate feedback, this allows for transmission at high data rates. Trading data rates for communication latency, a communication link may however avoid feedback and instead operate under channel uncertainty, in which case the accurate model is the compound channel. Further reductions of latency may be harnessed from quantum receiver design. In this work we focus in particular on the application of the sequential decoding approach to the bosonic compound channel with unknown phase rotations, loss parameters and thermal noise values. We show that sequential decoding is optimal.
We consider a joint communication and sensing problem over an optical link in which a low-power transmitter simultaneously communicates with a receiver and identifies the range of a defect producing a backscattered signal. We model the system as a lossy thermal-noise bosonic channel, in which the target location, modeled as a beamsplitter, affects the timing of the backscattered signal. Motivated by the envisioned deployment of entanglement-enabled quantum networks, we allow the transmitter to exploit shared entanglement to assist both sensing and communication. Since entanglement is known to enhance sensing, as demonstrated in Quantum Illumination (QI), and to increase communication rates through entanglement-assisted communication, the transmitter faces a trade-off in allocating its entanglement resources between the two tasks. Our main result is a characterization of these trade-offs in the form of an achievable rate/error-exponent region, which can outperform time-sharing and demonstrates a quantum advantage.
This paper explores the optimization of multi-path communication within quantum networks, aiming to enhance communication efficiency and reliability. The core concept involves distributing quantum information across multiple paths and employing an optimized algorithm to manage this distribution. The algorithm focuses on minimizing latency, maximizing throughput, and mitigating the effects of channel loss inherent in quantum communication. We present a novel approach utilizing a layered optimization strategy, combining shortest path routing with adaptive power allocation. Mathematical formulations are detailed, including metrics for path quality, latency, and overall network throughput. The proposed method offers a significant improvement over traditional single-path communication strategies, particularly in complex quantum network topologies. Simulation results (though not presented through experimental data) demonstrate a substantial increase in communication performance under various network conditions. Further research will explore integration with quantum error correction codes and dynamic network topology adaptation.
The paper presents a pioneering approach in which classical signals and quantum signals based on discrete-variable QKD are simultaneously generated, transmitted, and received on a single wavelength. The performance of the hybrid transmission scheme is thoroughly investigated across various data rates and levels of channel attenuation. A secure key rate of 591 bps alongside a classical data rate of 125 kbps is experimentally realized by using commercial devices. Compared to existing methods, the proposed scheme optimizes the utilization of optical wave resources, reduces system costs, and effectively mitigates interference from optical communication signals on quantum signals.
Multiple-input multiple-output (MIMO) technology utilizes multiple antennas at the transmitter and receiver to enhance data transmission speeds and reliability. Traditional MIMO decoding methods, however, can become increasingly complex as the number of antennas and modulation order rises. Quantum computing brings forth a new realm of information processing with significant potential. This study investigates the applicability of quantum algorithms for decoding information in MIMO wireless communication systems. Specifically, the Dürr-Høyer quantum search, based on Grover’s algorithm, and optimal quantum sorting algorithms are leveraged to reduce the query complexity with an analysis of the complexity and achievable bit error rate performance of the quantum-assisted decoders. The study considers cases of MIMO diversity, spatial modulation, and multiplexing transmission using both maximum-likelihood and fixed-complexity sphere decoders. By examining a variety of communication scenarios, this work aims to assess the applicability of quantum algorithms across different operational regimes and aids in extending the methodology to other communication systems.
Wireless communication above 300GHz requires highly sophisticated analog circuit design due to severe frequency dependent ohmic losses. The complexity of such electronic hardware motivates exploring wireless quantum optical communication approaches even for the 6G “terahertz (THz) range” 300GHz,10THz. In this work, the classical radio frequency (RF)-based inner physical layer (PHY) transceiver blocks of channel coded wireless communication systems are replaced by wireless quantum optical transceiver blocks. Short range concepts employing LEDs as transmitters are particularly attractive, owing to their low implementation cost and practical simplicity. In contrast to laser based wireless quantum optical transmission over multipath channels, the quantum mechanical density operator ρ̲RX,[si,bi] and the transition probability γ(si,si+1) required by the quantum data detection must be revised accordingly. Furthermore, the novel interpretation introduced here, in which the extrinsic information is treated as a diversity branch rather than as an estimate of the a priori information, facilitates turbo equalization that still can accomodate varying a priori information. However, due to the limited uncoded transmission performance achievable with such systems, the incorporation of sophisticated channel coding schemes appears imperative. The authors therefore investigate the combination of sophisticated channel coding techniques, such as polar coding, with LED based wireless quantum optical transmission technologies. All numerical results assume a cryogenically cooled receiver front-end (approximately 10 K), yielding thermal noise levels. Operation at room temperature in the 6G THz range 300GHz,10THz would require an average number N¯α of thermal noise photon values of approximately 5 to 20, which is beyond the scope of this feasibility study. The results show that the proposed paradigm enables simple, robust, and practically viable wireless quantum optical communication systems with favorable transmission performance. Additional gains are achieved through iterative turbo equalization. The results also suggest that the proposed approach can pave the way toward robust and economically viable future communication solutions.