We introduce a two-parameter family of discrepancy measures, termed \emph{$(G,f)$-divergences}, obtained by applying a non-decreasing function $G$ to an $f$-divergence $D_f$. Building on Csiszár's formulation of mutual $f$-information, we define a corresponding $(G,f)$-information measure $ I_{G,f}(X;Y)$. A central theme of the paper is subadditivity over product distributions and product channels. We develop reduction principles showing that, for broad classes of $G$, it suffices to verify divergence subadditivity on binary alphabets. Specializing to the functions $G(x)\in\{x,\log(1+x),-\log(1-x)\}$, we derive tractable sufficient conditions on $f$ that guarantee subadditivity, covering many standard $f$-divergences. Finally, we present applications to finite-blocklength converses for channel coding, bounds in binary hypothesis testing, and an extension of the Shannon--Gallager--Berlekamp sphere-packing exponent framework to subadditive $(G,f)$-divergences.

Random binning is a widely used technique in information theory with diverse applications. In this paper, we focus on the output statistics of random binning (OSRB) using the Tsallis divergenceTα. We analyze all values of α ∈ (0,∞)∪{∞} and consider three scenarios: (i) the binned sequence is generated i.i.d., (ii) the sequence is randomly chosen from an ϵ-typical set, and (iii) the sequence originates from an ϵ-typical set and is passed through a non-memoryless virtual channel. Our proofs cover both achievability and converse results. To address the unbounded nature ofT∞, we extend the OSRB framework via Rényi’s divergence with order infinity, denotedD∞. As part of our exploration, we analyze a specific form of Rényi’s conditional entropy and its properties. Additionally, we demonstrate the application of this framework in deriving achievability results for the wiretap channel, where Tsallis divergence serves as a security measure. The secure rate we obtain through the OSRB analysis matches the secure capacity for α ∈ (0, 2] ∪ {∞} and serves as a potential candidate for the secure capacity when α ∈ (2,∞).

This paper undertakes a holistic investigation of two fundamental trade-offs in monostatic OFDM integrated sensing and communication (ISAC) systems, namely, the time-frequency trade-off and the spatial trade-off, originating from the choice of modulation order for random data and the design of beamforming strategies, respectively. To counteract the elevated side-lobe levels induced by varying-amplitude data in high-order QAM signaling, we introduce a novel linear minimum mean-squared-error (LMMSE) estimator. We also provide a rigorous theoretical characterization of side-lobe levels achieved by the proposed LMMSE estimator and two benchmark schemes, proving its superiority for any modulation scheme and SNR level. Moreover, we explore spatial domain trade-offs through two ISAC transmission strategies: concurrent, employing joint beams, and time-sharing, using separate beams for sensing and communications not overlapping in time. Simulations demonstrate improved performance of the LMMSE estimator, especially in detecting weak targets in the presence of strong ones with high-order QAM, consistently yielding more favorable ISAC trade-offs than existing baselines under various modulation schemes, SNR conditions, RCS levels and transmission strategies. Additionally, we present experimental results to validate the effectiveness of the LMMSE estimator in reducing side-lobe levels, based on real-world measurements

Random binning is a widely utilized tool in information theory, particularly for proving achievability bounds. In this paper, we investigate the output statistics of random binning (OSRB) for two cases: where the binned sequence is i.i.d. generated, and randomly chosen from an$\epsilon$-typical set using the Tsallis divergence$T_{\alpha}$measure for all values of$\alpha\in(0, \infty)$. For$\alpha=\infty$, due to the unbounded nature of$T_{\infty}$, we analyze the OSRB framework using Rényi's divergence criterion with the order of infinity, denoted as$D_{\infty}$. While exploring OSRB, we encounter a specific form of Renyi's conditional entropy and delve into its properties. Additionally, we demonstrate the effectiveness of this framework in establishing achievability results for wiretap channels, where Tsallis divergence serves as a security measure. The secure rate we obtain is equal to the capacity for$\alpha\in(0.2]$.

Dynamic index coding is a practical generalization of conventional index coding that deals with real dynamic traffic streams. We identify the code-constrained capacity region of a dynamic index coding problem with a complete bi-directional side information graph and introduce the performance metric of dynamic index coding gain to measure how dynamic index coding reduces the required data transmissions. A greedy dynamic index coding scheme is proposed that achieves the maximum coding gain almost everywhere in the identified capacity region. Although the greedy scheme attains the maximum coding gain, its selfish nature may unacceptably increase transmission delay. To address this issue, a time-shared friendly dynamic index coding scheme is introduced that achieves the maximum coding gain over the entire capacity region and offers a lower delay than its greedy counterpart. To obtain the minimum delay, a constrained optimization problem is formulated to tune time-sharing weights in the friendly scheme. The closed-form solution of the optimization is derived for the special two-flow case. Furthermore, the results and analysis are extended to dynamic index coding problems with arbitrary side information graphs. We also use analytical and simulation results to provide graphical intuition for the obtained results.

A solution is presented to the spatial-wideband effect in line-of-sight multiple-input multiple-output transmission. This effect, which arises once the bandwidth is large enough that the propagation delay differences for distinct transmit-receive antenna pairs become comparable to the symbol period, causes frequency selectivity and intersymbol interference. The proposed solution, which only entails channel-independent DFT precoding and reception, plus delay lines, performs close to capacity for most array orientations and is compatible with both multicarrier and single-carrier signals.

This paper addresses the spatial-wideband effect in line-of-sight multiple-input multiple-output channels. This effect arises once the bandwidth is large enough that the differences in propagation delays for distinct transmit-receive antenna pairs cease to be negligible relative to the symbol period; this, in turn, gives rise to intersymbol interference. The impact of this effect is quantified as a function of the relevant geometric parameters (range, array orientations, antenna spacings) and a family of scalable solutions is proposed to counter it. In particular, a solution based on per-antenna delay lines at transmitter and receiver is shown to be highly effective, and a criterion is derived to set those delay lines as a function of the channel.

Drawing on the notion of parallel interference cancellation, this paper formulates a one-shot linear receiver for the uplink of centralized, possibly cloud-based, radio access networks (C-RANs) operating in a cell-free fashion. This receiver exhibits substantial interference rejection abilities, yet it does not involve any matrix inversions; rather, its structure hinges on the pairwise projections of the users' channel vectors. Its performance is markedly superior to that of matched-filter beamforming, while the computational cost is decidedly inferior to that of an MMSE filter, altogether constituting an attractive alternative in terms of performance vs cost. Furthermore, with a proper sparsification of the channel matrix that it estimates and processes, the proposed receiver can be rendered scalable in the sense of its computational cost per access point not growing with size of the network. Uplink power control is also readily accommodated.

This paper tackles the problem of zero-forcing (ZF) precoding for the downlink of centralized radio-access networks operating in a cell-free fashion. While the customary workhorse of ZF precoding is the channel pseudo-inverse, because of the separate power constraint at each participating access point, the pseudo-inverse is not optimum. Rather, it can be improved upon by other inverses that allow conveying stronger signals (or, equivalently, consuming less power) while respecting the same ZF conditions. Motivated by the enormous disparity in computational cost between simple pseudo-inversion and general inversion, we ascertain the performance disadvantage of the former in a wide range of conditions. The welcome conclusion is that pseudo-inversion is close-to-optimum for all operational regimes of interest.

In this paper, a new measure of correlation is introduced. This measure depends on a parameter α, and is defined in terms of vector-valued Lpnorms. The measure is within a constant of the exponential of α-Rényi mutual information, and reduces to the trace norm (total variation distance) for α = 1. We provide some properties and applications of this measure of correlation. In particular, we establish a bound on the secrecy exponent of the wiretap channel (under the total variation metric) in terms of the α-Rényi mutual information according to Csiszár's proposal.

In this paper, we introduce a new measure of correlation for bipartite quantum states. This measure depends on a parameter$\alpha $, and is defined in terms of vector-valued$\textit {L}_{\textit {p}}$-norms. The measure is within a constant of the exponential of$\alpha $-Rényi mutual information, and reduces to the trace norm (total variation distance) for$\alpha =1$. We will prove some decoupling type theorems in terms of this measure of correlation, and present some applications in privacy amplification as well as in bounding the random coding exponents. In particular, we establish a bound on the secrecy exponent of the wiretap channel (under the total variation metric) in terms of the$\alpha $-Rényi mutual information according toCsiszár’s proposal.

In this paper, we consider a secure network coding problem in which some secret keys are shared among legitimate nodes, and there exists an eavesdropper which is able to hear a subset of links. We show the equivalency of secure network coding under weak and strong secrecy conditions. For linear network coding, we show a stronger result: equivalency of "perfect secrecy and zero-error constraints" to "weak secrecy and $epsilon$-error constraints". This is a secure version of the result obtained by Langberg and Effros, on the equivalence of zero-error and $epsilon$-error regions in the network coding problem with co-located sources. Jalali and Ho exploit extractor functions to prove the weak and strong rate region equivalency for this network; however, to prove this equivalency, we develop some tools in random binning and prove the equivalency in a slightly more general setting.

In this paper, we investigate the index coding problem in the presence of an eavesdropper. Messages are to be sent from one transmitter to a number of legitimate receivers who have side information about the messages, and share a set of secret keys with the transmitter. To do this, the transmitter communicates to the legitimate receivers the public code C, which is also heard by the eavesdropper. We assume perfect secrecy, meaning that the eavesdropper should not be able to retrieve any information about the message set from the public communication. We study the minimum key lengths for zero-error and perfectly secure index coding problem. On one hand, this problem is a generalization of the index coding problem (and thus a difficult one). On the other hand, it is a generalization of the Shannon's cipher system. We show that a generalization of Shannon's one-time pad strategy is optimal up to a multiplicative constant, meaning that it obtains the entire boundary of the cone formed by looking at the secure rate region from the origin. This shows the optimality of the generalized one-time pad for minimizing the consumption of shared secret keys per message bits, when public communication is free (the transmitter is not charged for the rate of the public communication). Finally, we consider relaxation of the perfect secrecy and zero-error constraints to weak secrecy and asymptotically vanishing probability of error, and provide a secure version of the result, obtained by Langberg and Effros, on the equivalence of zero-error and ε-error regions in the conventional index coding problem.

In this paper, we investigate the index coding problem in the presence of an eavesdropper. Messages are to be sent from one transmitter to a number of legitimate receivers who have side information about the messages, and share a set of secret keys with the transmitter. We assume perfect secrecy, meaning that the eavesdropper should not be able to retrieve any information about the message set. This problem is a generalization of the Shannon's cipher system. We study the minimum key lengths for zero-error and perfectly secure index coding problems.