We study a basic joint communication and sensing setup from an information theoretic perspective. A transmitter sends an encoded message through a pair of noisy channels connected to a receiver and a sensor. The receiver is interested in decoding the message from its noisy observation. The sensor has access to the message as side information, and instead is interested in estimating an unknown yet fixed binary state of its channel.
This paper considers a single-source single-destination half-duplex $n$ -relay network with arbitrary topology, where the source communicates with the destination through a direct link and with the help of $n$ half-duplex relays. The focus is on the linear deterministic approximation of the Gaussian noise network model.
In this paper, we study a distributed learning problem constrained by constant communication bits. Specifically, we consider the distributed hypothesis testing (DHT) problem where two distributed nodes are constrained to transmit a constant number of bits to a central decoder. In such settings, we show that in order to achieve the optimal error exponents, it suffices to consider the empirical distributions of observed data sequences and encode them to the transmission bits.
This paper studies the capacity scaling of non-coherent Single-Input Multiple-Output (SIMO) independent and identically distributed (i.i.d.) Rayleigh block fading channels versus bandwidth ( $B$ ), number of receive antennas ( $N$ ) and coherence block length ( $L$ ). In non-coherent channels (without Channel State Information鈥揅SI) capacity scales as $\Theta (\min (B,\sqrt {NL},N))$ . This is achievable using Pilot-Assisted signaling. Energy Modulation signaling rate scales as $\Theta (\min (B,\sqrt {N}))$ .
Understanding the fundamental limits of technologies enabling future wireless communication systems is essential for their efficient state-of-the-art design. A prominent technology of major interest in this framework is non-orthogonal multiple access (NOMA). In this paper, we derive an explicit rigorous closed-form analytical expression for the optimum spectral efficiency, in the large-system limit, of regular sparse (code-domain) NOMA, along with a closed-form formulation for the limiting spectral density of the underlying input covariance matrix.
Most DNA sequencing technologies are based on the shotgun paradigm: many short reads are obtained from random unknown locations in the DNA sequence. A fundamental question, in Motahari et al., (2013), is what read length and coverage depth (i.e., the total number of reads) are needed to guarantee reliable sequence reconstruction. Motivated by DNA-based storage, we study the coded version of this problem; i.e., the scenario where the DNA molecule being sequenced is a codeword from a predefined codebook.
This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.
It is our pleasure to share with you this special issue, providing a snapshot of the current evolution of coding for data management and delivery in networks. Using coding to provide flexibility and efficiency in data management, rather than merely as tool to combat locally bit rot or transmission impediments, has become an increasingly rich and active domain of investigation. It weaves themes of protocol design, resource allocation, quality of experience management and code construction.