Information Theory (cs.IT)

Abstract: Timely sampling and fresh information delivery are important in 6G communications. This is achieved by encoding samples into short packets/codewords for transmission, with potential decoding errors. We consider a broadcasting base station (BS) that samples information from multiple sources and transmits to respective destinations/users, using short-blocklength cyclic and deep learning (DL) based codes for error correction, and cyclic-redundancy-check (CRC) codes for error detection. We use a metric called reported age of information (AoI), abbreviated as RAoI, to measure the freshness of information, which increases from an initial value if the CRC reports a failure, else is reset. We minimize long-term average expected RAoI, subject to constraints on transmission power and distortion, for which we obtain age-agnostic randomized and age-aware drift-plus-penalty policies that decide which user to transmit to, with what message-word length and transmit power, and derive bounds on their performance. Simulations show that longer CRC codes lead to higher RAoI, but the RAoI achieved is closer to the true, genie-aided AoI. DL-based codes achieve lower RAoI. Finally, we conclude that prior AoI optimization literature with finite blocklengths substantially underestimates AoI because they assume that all errors can be detected perfectly without using CRC.

Abstract: This work studies the meta distribution (MD) in a two-user partial non-orthogonal multiple access (pNOMA) network. Compared to NOMA where users fully share a resource-element, pNOMA allows sharing only a fraction $\alpha$ of the resource-element. The MD is computed via moment-matching using the first two moments where reduced integral expressions are derived. Accurate approximates are also proposed for the $b{\rm th}$ moment for mathematical tractability. We show that in terms of percentile-performance of links, pNOMA only outperforms NOMA when $\alpha$ is small. Additionally, pNOMA improves the percentile-performance of the weak-user more than the strong-user highlighting its role in improving fairness.

Abstract: Variable-to-variable length (VV) codes are a class of lossless source coding. As their name implies, VV codes encode a variable-length sequence of source symbols into a variable-length codeword. This paper will give a complete proof of an important theorem for variable-to-variable length codes.

Abstract: Satellite-terrestrial integrated networks (STINs) are promising architecture for providing global coverage. In STINs, full frequency reuse between a satellite and a terrestrial base station (BS) is encouraged for enhancing spectral efficiency, which accounts for non-negligible amount of interference. To address the interference management problem in STINs, this paper proposes a novel distributed precoding method. Key features of our method are: i) a rate-splitting (RS) strategy is incorporated for efficient interference management, ii) precoders are designed in a distributed way without sharing channel state information between a satellite and a terrestrial BS. Specifically, to design precoders in a distributed fashion, we put forth a spectral efficiency decoupling technique. This technique disentangles the total spectral efficiency into two distinct terms, each dependent solely on the satellite's precoder and the terrestrial BS's precoder, respectively. Then, to resolve the non-smoothness raised by adopting the RS strategy, we approximate the spectral efficiency expression as a smooth function; thereafter we develop a generalized power iteration inspired optimization algorithm built based on the first-order optimality condition. Simulation results demonstrate that the proposed method improves the spectral efficiency (around 20~29%) compared to existing distributed precoding schemes.

Abstract: This paper focuses on the design of transmission methods and reflection optimization for a wireless system assisted by a single or multiple reconfigurable intelligent surfaces (RISs). The existing techniques are either too complex to implement in practical systems or too inefficient to achieve high performance. To overcome the shortcomings of the existing schemes, we propose a simple but efficient approach based on \textit{opportunistic reflection} and \textit{non-orthogonal transmission}. The key idea is opportunistically selecting the best user that can reap the maximal gain from the optimally reflected signals via RIS. That is to say, only the channel state information of the best user is used for RIS reflection optimization, which can in turn lower complexity substantially. In addition, the second user is selected to superpose its signal on that of the primary user, where the benefits of non-orthogonal transmission, i.e., high system capacity and improved user fairness, are obtained. Additionally, a simplified variant exploiting random phase shifts is proposed to avoid the high overhead of RIS channel estimation.