The increase in the amount of data sent through the Internet is expected to scale up and accelerate in the coming years, along with the increasing number of connected devices. Current data rates via optical fiber communication channels are approaching the channel capacity and eventually, wireless communication will follow a similar trend. This means that message transmission may not be able to keep up with traffic demand in the future. Optimizing communication tasks and reducing the needed number of utilized radio resources will thus play a crucial role in goal-oriented communications. The latest theoretical and experimental works on message identification, a post-Shannon communication scheme, show promising results for addressing this problem. Under this scheme, the objective at the receiver is no longer to retrieve the content of the transmitted message, but to verify whether the sender is transmitting a specific message, in which the receiver may be interested or not. The sender does not know in advance which message the receiver is interested in. By using local randomness at the encoder, this allows for an exponential gain in the number of messages in identification compared to the available messages in classical transmission, potentially saving radio resources. In this paper, we review the pros and cons of identification and discuss its potential applications for task-oriented communications.
The increase in the amount of data sent through the Internet is expected to scale up and accelerate in the coming years, along with the increasing number of connected devices. Current data rates via optical fiber communication channels are approaching the channel capacity and eventually, wireless communication will follow a similar trend. This means that message transmission may not be able to keep up with traffic demand in the future. Optimizing communication tasks and reducing the needed number of utilized radio resources will thus play a crucial role in goal-oriented communications. The latest theoretical and experimental works on message identification, a post-Shannon communication scheme, show promising results for addressing this problem. Under this scheme, the objective at the receiver is no longer to retrieve the content of the transmitted message, but to verify whether the sender is transmitting a specific message, in which the receiver may be interested or not. The sender does not know in advance which message the receiver is interested in. By using local randomness at the encoder, this allows for an exponential gain in the number of messages in identification compared to the available messages in classical transmission, potentially saving radio resources. In this paper, we review the pros and cons of identification and discuss its potential applications for task-oriented communications.
We analyze message identification via Gaussian channels with noiseless feedback, which is part of the Post Shannon theory. The consideration of communication systems beyond Shannon's approach is useful in order to increase the efficiency of information transmission for certain applications. If the noise variance is positive, we propose a coding scheme that generates infinite common randomness between the sender and the receiver. We show that any identification rate via the Gaussian channel with noiseless feedback can be achieved. The remarkable result is that this applies to both rate definitionsn1logM(as defined by Shannon for transmission) andn1loglogM— (as defined by Ahlswede and Dueck for identification). We can even show that our result holds regardless of the selected scaling for the rate. A detailed version with all proofs, explanations and more discussions can be found in [1].
We analyze message identification via Gaussian channels with noiseless feedback, which is part of the Post Shannon theory. The consideration of communication systems beyond Shannon's approach is useful in order to increase the efficiency of information transmission for certain applications. If the noise variance is positive, we propose a coding scheme that generates infinite common randomness between the sender and the receiver. We show that any identification rate via the Gaussian channel with noiseless feedback can be achieved. The remarkable result is that this applies to both rate definitions n1logM (as defined by Shannon for transmission) and n1loglogM — (as defined by Ahlswede and Dueck for identification). We can even show that our result holds regardless of the selected scaling for the rate. A detailed version with all proofs, explanations and more discussions can be found in [1].
Classical identification via a noisy channel is a communication task in which the receiver is not required to reconstruct the full transmitted message, but only to decide whether it coincides with a message of interest. This relaxation allows the number of identifiable messages to grow doubly exponentially with the blocklength. For quantum channels, the resulting (doubly exponential) identification capacity CID can strictly exceed the ordinary (exponential) transmission capacity C.
In this paper, we prove that the entanglement-assisted transmission capacity CE is a strong converse bound for this task: CID≤CE. For sufficiently low-noise channels, this bound can also be achieved via the Hayden-Winter (quantum) identification + fingerprinting codes. This yields an exact characterization CID=CE of identification capacity for such channels. However, for general channels, we prove that this upper bound can be strict. We exhibit an explicit family of transpose-depolarizing channels for which CID<CE. As a consequence, we also obtain the first example of strict superadditivity of the identification capacity CID.
Common randomness (CR), as a resource, is not commonly used in existing practical communication systems. In the common randomness framework, both sender and receiver, often described as terminals, aim to generate a common random variable observable to both, perhaps with low error probability. The knowledge of this CR allows to implement correlated random protocols that could lead to faster and more efficient algorithms. We characterize CR over Gaussian channels for their practical relevance in many communication situations by deriving the CR capacity for both Gaussian Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) cases. Furthermore, CR plays a key role in the identification scheme. In many new applications such as several machine-to-machine and human-to-machine systems and the tactile internet, which demand ultra-reliable low latency, the identification or also called post-Shannon scheme is proved to be more efficient than the classical transmission. It has been proved that through CR generation, the post-Shannon communication task allows to achieve an enormous performance gain. We consider a correlation-assisted secure identification scheme over Gaussian wiretap channels (GWC) and develop a lower bound on the corresponding secure identification capacity.
Born about a century ago, Quantum Mechanics has revolutionized the description and the interpretation of Physics at sub-microscopic level. In the last decades, due to the influence of mathematical and engineering research fields, Quantum Mechanics has given birth to related research areas like Quantum Computation, Quantum Information and Quantum Communication. With the discovery of the laser, and later the development of fiber optics and satellite networks, Quantum Communication and Quantum Optics seems to have a natural field of application in Communication Systems. Despite this, the interest in this technology and studies for communication purpose has been overshadowed by the great results in communication networks achieved in the last decades with classical paradigms. However, due to the increasing demand of communication data rate, system designers are now looking at Quantum Mechanics for new and more performanting solutions in communication purposes. Early theoretical studies on Quantum Discrimination Theory and Quantum Information predict better performance for Communication Systems that take advantage of the quantum laws. In addition, Quantum Mechanics provides the deepest description of the physical phenomena, and there are scenarios where a quantum model fits best, as in in deep space communications, where the received signal is really weak, or in a satellite networks, where we are interested in strongly reducing the power of transmitted signals, possibly without sacrificing performance significantly. However, if on one side Quantum Communication Theory promises great gains in the performance of communication systems, on the other hand it fails to describe how to implement physical devices that reach these ultimate limits. So far, only a few architectures achieving these performances are known, and only for simple modulation formats. We are interested in the scenario of optical communications, where the message transmitted is encoded in a sequence of coherent states. Transmitter devices for coherent modulation are well known and consist in laser pulse generators. Instead, receiver implementations working at the quantum limit performance limit are yet to be found. In this Thesis I deal with different topics in the quantum transmission scenario. First, I review existing classical (suboptimal) and quantum (suboptimal and optimal) receiver schemes for the binary coherent modulation. I present a new formulation of the optimal scheme known as Dolinar Receiver with the multiple copies problem, focusing on the information gained during the measurement. Second, I analyze the binary communication in a noisy environment, studying the error probability and the capacity of the binary channel induced. Given the description of the quantum channel, I optimize both the transmitted quantum states and the measurement operators employed in the communication. Third, I consider the Pulse Position Modulation, that is particularly suitable for space and satellite communication due to its simplicity of implementation and high capacity. I review some known suboptimal receivers, and I propose a receiver scheme which approaches the limit performance predicted with quantum theory outperforming the existing schemes. To sum up the results of this Thesis, in order to approach the limit performance predicted by Quantum Mechanics, an optimization is always necessary to exceed the classical effects and trigger the quantum phenomena. In particular, the information gained during the measurement plays an important role, for example in the definition of adaptive receivers. In this Thesis both these aspects have been deeply investigated.
We investigate message identification over a K-sender Gaussian multiple access channel (K-GMAC). Unlike conventional Shannon transmission codes, the size of randomized identification (ID) codes experiences a doubly exponential growth in the code length. Improvements in the ID approach can be attained through additional resources such as quantum entanglement, common randomness (CR), and feedback. It has been demonstrated that an infinite capacity can be attained for a single-user Gaussian channel with noiseless feedback, irrespective of the chosen rate scaling. We establish the capacity region of both the K-sender Gaussian multiple access channel (K-GMAC) and the K-sender state-dependent Gaussian multiple access channel (K-SD-GMAC) when strictly causal noiseless feedback is available.