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Graph burning is a discrete-time process on graphs where vertices are sequentially activated and burning vertices cause their neighbours to burn over time. In this work, we focus on a dynamic setting in which the graph grows over time, and at each step we burn vertices in the growing grid $G_n = [-f(n),f(n)]^2$. We investigate the set of achievable burning densities for functions of the form $f(n)=\lceil cn^α\rceil$, where $α\ge 1$ and $c>0$. We show that for $α=1$, the set of achievable densities is $[1/(2c^2),1]$, for $1<α<3/2$, every density in $[0,1]$ is achievable, and for $α=3/2$, the set of achievable densities is $[0,(1+\sqrt{6}c)^{-2}]$.
This paper studies achievable rates of nanopore-based DNA storage when nanopore signals are decoded using a tractable channel model that does not rely on a basecalling algorithm. Specifically, the noisy nanopore channel (NNC) with the Scrappie pore model generates average output levels via i.i.d. geometric sample duplications corrupted by i.i.d. Gaussian noise (NNC-Scrappie). Simplified message passing algorithms are derived for efficient soft decoding of nanopore signals using NNC-Scrappie. Previously, evaluation of this channel model was limited by the lack of DNA storage datasets with nanopore signals included. This is solved by deriving an achievable rate based on the dynamic time-warping (DTW) algorithm that can be applied to genomic sequencing datasets subject to constraints that make the resulting rate applicable to DNA storage. Using a publicly-available dataset from Oxford Nanopore Technologies (ONT), it is demonstrated that coding over multiple DNA strands of $100$ bases in length and decoding with the NNC-Scrappie decoder can achieve rates of at least $0.64-1.18$ bits per base, depending on the channel quality of the nanopore that is chosen in the sequencing device per c
Guessing random additive noise decoding (GRAND) has received widespread attention recently, and among its variants, ordered reliability bits GRAND (ORBGRAND) is particularly attractive due to its efficient utilization of soft information and its amenability to hardware implementation. It has been recently shown that ORBGRAND is almost capacity-achieving in additive white Gaussian noise channels under antipodal input. In this work, we first extend the analysis of ORBGRAND achievable rate to memoryless binary-input bit channels with general output conditional probability distributions. The analytical result also sheds insight into understanding the gap between the ORBGRAND achievable rate and the channel mutual information. As an application of the analysis, we study the ORBGRAND achievable rate of bit-interleaved coded modulation (BICM). Numerical results indicate that for BICM, the gap between the ORBGRAND achievable rate and the channel mutual information is typically small, and hence suggest the feasibility of ORBGRAND for channels with high-order coded modulation schemes.
Examples of achievable Cantorvals are constructed with reversed Kakeya conditions only on a set of asymptotic density zero which answers in positive the Problem 5.2 from Marchwicki and Miska (2021). Additionally, the Lebesgue measure of the boundaries of these Cantorvals is found to be zero which does not answer the still open problem of existence of achievable Cantorvals with boundaries of positive measure.
The generalized linear system (GLS) has been widely used in wireless communications to evaluate the effect of nonlinear preprocessing on receiver performance. Generalized approximation message passing (AMP) is a state-of-the-art algorithm for the signal recovery of GLS, but it was limited to measurement matrices with independent and identically distributed (IID) elements. To relax this restriction, generalized orthogonal/vector AMP (GOAMP/GVAMP) for unitarily-invariant measurement matrices was established, which has been proven to be replica Bayes optimal in uncoded GLS. However, the information-theoretic limit of GOAMP/GVAMP is still an open challenge for arbitrary input distributions due to its complex state evolution (SE). To address this issue, in this paper, we provide the achievable rate analysis of GOAMP/GVAMP in GLS, establishing its information-theoretic limit (i.e., maximum achievable rate). Specifically, we transform the fully-unfolded state evolution (SE) of GOAMP/GVAMP into an equivalent single-input single-output variational SE (VSE). Using the VSE and the mutual information and minimum mean-square error (I-MMSE) lemma, the achievable rate of GOAMP/GVAMP is derived. M
For the two-user multiple-input multiple-output (MIMO) broadcast channel with delayed channel state information at the transmitter (CSIT) and arbitrary antenna configurations, all the degrees-of-freedom (DoF) regions are obtained. However, for the three-user MIMO broadcast channel with delayed CSIT and arbitrary antenna configurations, the DoF region of order-2 messages is still unclear and only a partial achievable DoF region of order-1 messages is obtained, where the order-2 messages and order-1 messages are desired by two receivers and one receiver, respectively. In this paper, for the three-user MIMO broadcast channel with delayed CSIT and arbitrary antenna configurations, we first design transmission schemes for order-2 messages and order-1 messages. Next, we propose to analyze the achievable DoF region of transmission scheme by transformation approach. In particular, we transform the decoding condition of transmission scheme w.r.t. phase duration into the achievable DoF region w.r.t. achievable DoF, through achievable DoF tuple expression connecting phase duration and achievable DoF. As a result, the DoF region of order-2 messages is characterized and an achievable DoF region
The K-user flat fading MIMO interference channel with J instantaneous relays (KICJR) is considered. In the KICJR, the effective channel between sources and destinations including the relays has certain structure and is non-generic. For non-generic channels, the achievable degrees of freedom (DoF) is still unknown. Lee and Wang showed that by using the aligned interference neutralization scheme 3/2 degrees of freedom is achievable in a 2IC1R system, which is 50% more than the 2-user interference channel. But the DoF performance and achievable schemes for other KICJR networks are not investigated in literature. In this paper we devise an achievable scheme called restricted interference alignment for instantaneous-relay aided interference channels. Also, to find insights to the maximum achievable degrees of freedom we develop linear beamforming based on the mean square error (MSE) minimization as an achievable scheme. Furthermore, we present upper-bounds on the maximum achievable degrees of freedom by investigating the properness of the interference alignment equation system. The numerical results show that the DoF performance of the proposed restricted interference alignment scheme a
In this paper, we study the achievable rate region of Gaussian multiuser channels with the messages transmitted being from finite input alphabets and the outputs being {\em quantized at the receiver}. In particular, we focus on the achievable rate region of $i)$ Gaussian broadcast channel (GBC) and $ii)$ Gaussian multiple access channel (GMAC). First, we study the achievable rate region of two-user GBC when the messages to be transmitted to both the users take values from finite signal sets and the received signal is quantized at both the users. We refer to this channel as {\em quantized broadcast channel (QBC)}. We observe that the capacity region defined for a GBC does not carry over as such to QBC. We show that the optimal decoding scheme for GBC (i.e., high SNR user doing successive decoding and low SNR user decoding its message alone) is not optimal for QBC. We then propose an achievable rate region for QBC based on two different schemes. We present achievable rate region results for the case of uniform quantization at the receivers. Next, we investigate the achievable rate region of two-user GMAC with finite input alphabet and quantized receiver output. We refer to this chann
We study the mismatched successive refinement problem where one uses Gaussian codebooks to compress an arbitrary memoryless source with successive minimum Euclidean distance encoding under the quadratic distortion measure. Specifically, we derive achievable refined asymptotics under both the joint excess-distortion probability (JEP) and the separate excess-distortion probabilities (SEP) criteria. For both second-order and moderate deviations asymptotics, we consider two types of codebooks: the spherical codebook where each codeword is drawn independently and uniformly from the surface of a sphere and the i.i.d. Gaussian codebook where each component of each codeword is drawn independently from a Gaussian distribution. We establish the achievable second-order rate-region under JEP and we show that under SEP any memoryless source satisfying mild moment conditions is strongly successively refinable. When specialized to a Gaussian memoryless source (GMS), our results provide an alternative achievability proof with specific code design. We show that under JEP and SEP, the same moderate deviations constant is achievable. For large deviations asymptotics, we only consider the i.i.d. Gauss
In this paper we look at the topological type of algebraic sum of achievement sets. We show that there is a Cantorval such that the algebraic sum of its $k$ copies is still a Cantorval for any $k \in \mathbb{N}$. We also prove that for any $m,p \in (\mathbb{N}\setminus \{1\}) \cup \{\infty\}$, $p \geq m$, the algebraic sum of $k$ copies of a Cantor set can transit from a Cantor set to a Cantorval for $k=m$ and then to an interval for $k=p$. These two main results are based on a new characterization of sequences whose achievement sets are Cantorvals. We also define a new family of achievable Cantorvals which are not generated by multigeometric series. In the final section we discuss various decompositions of sequences related to the topological typology of achievement sets.
What sets A \subset Z^n can be written in the form (K-K) \cap Z^n, where K is a compact subset of R^n such that K+Z^n=R^n? Such sets A are called achievable, and it is known that if A is achievable, then < A >=Z^n. This condition completely characterizes achievable sets for n=1, but not much is known for n \ge 2. We attempt to characterize achievable sets further by showing that with any finite, symmetric set A \subset Z^n containing zero, we may associate a graph G(A). Then if A is achievable, we show the set associated to some connected component of G(A) is achievable. In two dimensions, we can strengthen this theorem further. Further generalizations and open questions are discussed. Throughout, the language and formalism of algebraic topology are useful.
In this paper, the achievable DoF of MIMO X channels for constant channel coefficients with $M_t$ antennas at transmitter $t$ and $N_r$ antennas at receiver $r$ ($t,r=1,2$) is studied. A spatial interference alignment and cancelation scheme is proposed to achieve the maximum DoF of the MIMO X channels. The scenario of $M_1\geq M_2\geq N_1\geq N_2$ is first considered and divided into 3 cases, $3N_2<M_1+M_2<2N_1+N_2$ (Case $A$), $M_1+M_2\geq2N_1+N_2$ (Case $B$), and $M_1+M_2\leq3N_2$ (Case $C$). With the proposed scheme, it is shown that in Case $A$, the outer-bound $\frac{M_1+M_2+N_2}{2}$ is achievable; in Case $B$, the achievable DoF equals the outer-bound $N_1+N_2$ if $M_2>N_1$, otherwise it is 1/2 or 1 less than the outer-bound; in Case $C$, the achievable DoF is equal to the outer-bound $2/3(M_1+M_2)$ if $(3N_2-M_1-M_2)\mod 3=0$, and it is 1/3 or 1/6 less than the outer-bound if $(3N_2-M_1-M_2)\mod 3=1 \mathrm{or} 2$. In the scenario of $M_t\leq N_r$, the exact symmetrical results of DoF can be obtained.
In this paper, we study a general additive state-dependent Gaussian interference channel (ASD-GIC) where we consider two-user interference channel with two independent states known non-causally at both transmitters, but unknown to either of the receivers. An special case, where the additive states over the two links are the same is studied in [1], [2], in which it is shown that the gap between the achievable symmetric rate and the upper bound is less than 1/4 bit for the strong interference case. Here, we also consider the case where each channel state has unbounded variance [3], which is referred to as the strong interferences. We first obtain an outer bound on the capacity region. By utilizing lattice-based coding schemes, we obtain four achievable rate regions. Depend on noise variance and channel power constraint, achievable rate regions can coincide with the channel capacity region. For the symmetric model, the achievable sum-rate reaches to within 0.661 bit of the channel capacity for signal to noise ratio (SNR) greater than one.
We study the problem of universal decoding for unknown discrete memoryless channels in the presence of erasure/list option at the decoder, in the random coding regime. Specifically, we harness a universal version of Forney's classical erasure/list decoder developed in earlier studies, which is based on the competitive minimax methodology, and guarantees universal achievability of a certain fraction of the optimum random coding error exponents. In this paper, we derive an exact single-letter expression for the maximum achievable fraction. Examples are given in which the maximal achievable fraction is strictly less than unity, which imply that, in general, there is no universal erasure/list decoder which achieves the same random coding error exponents as the optimal decoder for a known channel. This is in contrast to the situation in ordinary decoding (without the erasure/list option), where optimum exponents are universally achievable, as is well known. It is also demonstrated that previous lower bounds derived for the maximal achievable fraction are not tight in general. We then analyze a generalized random coding ensemble which incorporate a training sequence, in conjunction with
In this work, we consider a discrete-time stationary Rayleigh flat-fading channel with unknown channel state information at transmitter and receiver. The law of the channel is presumed to be known to the receiver. In addition, we assume the power spectral density (PSD) of the fading process to be compactly supported. For i.i.d. zero-mean proper Gaussian input distributions, we investigate the achievable rate. One of the main contributions is the derivation of two new upper bounds on the achievable rate with zero-mean proper Gaussian input symbols. The first one holds only for the special case of a rectangular PSD and depends on the SNR and the spread of the PSD. Together with a lower bound on the achievable rate, which is achievable with i.i.d. zero-mean proper Gaussian input symbols, we have found a set of bounds which is tight in the sense that their difference is bounded. Furthermore, we show that the high SNR slope is characterized by a pre-log of 1-2f_d, where f_d is the normalized maximum Doppler frequency. This pre-log is equal to the high SNR pre-log of the peak power constrained capacity. Furthermore, we derive an alternative upper bound on the achievable rate with i.i.d.
The problem of mismatched decoding for discrete memoryless channels is addressed. A mismatched cognitive multiple-access channel is introduced, and an inner bound on its capacity region is derived using two alternative encoding methods: superposition coding and random binning. The inner bounds are derived by analyzing the average error probability of the code ensemble for both methods and by a tight characterization of the resulting error exponents. Random coding converse theorems are also derived. A comparison of the achievable regions shows that in the matched case, random binning performs as well as superposition coding, i.e., the region achievable by random binning is equal to the capacity region. The achievability results are further specialized to obtain a lower bound on the mismatch capacity of the single-user channel by investigating a cognitive multiple access channel whose achievable sum-rate serves as a lower bound on the single-user channel's capacity. In certain cases, for given auxiliary random variables this bound strictly improves on the achievable rate derived by Lapidoth.
In this paper, we propose an achievable rate region for discrete memoryless interference channels with conferencing at the transmitter side. We employ superposition block Markov encoding, combined with simultaneous superposition coding, dirty paper coding, and random binning to obtain the achievable rate region. We show that, under respective conditions, the proposed achievable region reduces to Han and Kobayashi achievable region for interference channels, the capacity region for degraded relay channels, and the capacity region for the Gaussian vector broadcast channel. Numerical examples for the Gaussian case are given.
This paper considers the achievable rates and decoding complexity of low-density parity-check (LDPC) codes over statistically independent parallel channels. The paper starts with the derivation of bounds on the conditional entropy of the transmitted codeword given the received sequence at the output of the parallel channels; the component channels are considered to be memoryless, binary-input, and output-symmetric (MBIOS). These results serve for the derivation of an upper bound on the achievable rates of ensembles of LDPC codes under optimal maximum-likelihood (ML) decoding when their transmission takes place over parallel MBIOS channels. The paper relies on the latter bound for obtaining upper bounds on the achievable rates of ensembles of randomly and intentionally punctured LDPC codes over MBIOS channels. The paper also provides a lower bound on the decoding complexity (per iteration) of ensembles of LDPC codes under message-passing iterative decoding over parallel MBIOS channels; the bound is given in terms of the gap between the rate of these codes for which reliable communication is achievable and the channel capacity. The paper presents a diagram which shows interconnection
The paper introduces new bounds on the asymptotic density of parity-check matrices and the achievable rates under ML decoding of binary linear block codes transmitted over memoryless binary-input output-symmetric channels. The lower bounds on the parity-check density are expressed in terms of the gap between the channel capacity and the rate of the codes for which reliable communication is achievable, and are valid for every sequence of binary linear block codes. The bounds address the question, previously considered by Sason and Urbanke, of how sparse can parity-check matrices of binary linear block codes be as a function of the gap to capacity. The new upper bounds on the achievable rates of binary linear block codes tighten previously reported bounds by Burshtein et al., and therefore enable to obtain tighter upper bounds on the thresholds of sequences of binary linear block codes under ML decoding. The bounds are applied to low-density parity-check (LDPC) codes, and the improvement in their tightness is exemplified numerically.
In this paper we investigate the achievable rate of a system that includes a nomadic transmitter with several antennas, which is received by multiple agents, exhibiting independent channel gains and additive circular-symmetric complex Gaussian noise. In the nomadic regime, we assume that the agents do not have any decoding ability. These agents process their channel observations and forward them to the final destination through lossless links with a fixed capacity. We propose new achievable rates based on elementary compression and also on a Wyner-Ziv (CEO-like) processing, for both fast fading and block fading channels, as well as for general discrete channels. The simpler two agents scheme is solved, up to an implicit equation with a single variable. Limiting the nomadic transmitter to a circular-symmetric complex Gaussian signalling, new upper bounds are derived for both fast and block fading, based on the vector version of the entropy power inequality. These bounds are then compared to the achievable rates in several extreme scenarios. The asymptotic setting with numbers of agents and transmitter's antennas taken to infinity is analyzed. In addition, the upper bounds are analyt