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We consider a downlink multi-user scenario and investigate the use of reconfigurable intelligent surfaces (RISs) to maximize the dirty-paper-coding (DPC) sum rate of the RIS-assisted broadcast channel. Different from prior works, which maximize the rate achievable by linear precoders, we assume a capacity-achieving DPC scheme is employed at the transmitter and optimize the transmit covariances and RIS reflection coefficients to directly maximize the sum capacity of the broadcast channel. We propose an optimization algorithm that iteratively alternates between optimizing the transmit covariances using convex optimization and the RIS reflection coefficients using Riemannian manifold optimization. Our results show that the proposed technique can be used to effectively improve the sum capacity in a variety of scenarios compared to benchmark schemes.

Imperfect Channel State Information at the Transmitter (CSIT) is inevitable in modern wireless communication networks, and results in severe multi-user interference in multi-antenna Broadcast Channel (BC). While the capacity of multi-antenna (Gaussian) BC with perfect CSIT is known and achieved by Dirty Paper Coding (DPC), the capacity and the capacity-achieving strategy of multi-antenna BC with imperfect CSIT remain unknown. Conventional approaches therefore rely on applying communication strategies designed for perfect CSIT to the imperfect CSIT setting. In this work, we break this conventional routine and make two major contributions. First, we show that linearly precoded Rate-Splitting (RS), relying on the split of messages into common and private parts and linear precoding at the transmitter, and successive interference cancellation at the receivers, can achieve larger rate region than DPC in multi-antenna BC with partial CSIT. Second, we propose a novel scheme, denoted as Dirty Paper Coded Rate-Splitting (DPCRS), that relies on RS to split the user messages into common and private parts, and DPC to encode the private parts. We show that the rate region of DPCRS in Multiple-Input Single-Output (MISO) BC with partial CSIT is enlarged beyond that of conventional DPC and that of linearly precoded RS. Gaining benefits from the capability of RS to partially decode the interference and partially treat interference as noise, DPCRS is less sensitive to CSIT inaccuracies, networks loads and user deployments compared with DPC and other existing transmission strategies. [ABSTRACT FROM AUTHOR]

A multiple-input multiple-output (MIMO) version of the dirty paper channel is studied, where the channel input and the dirt experience the same fading process, and the fading channel state is known at the receiver. This represents settings where signal and interference sources are co-located, such as in the broadcast channel. First, a variant of Costa’s dirty paper coding is presented, whose achievable rates are within a constant gap to capacity for all signal and dirt powers. In addition, a lattice coding and decoding scheme is proposed, whose decision regions are independent of the channel realizations. Under Rayleigh fading, the gap to capacity of the lattice coding scheme vanishes with the number of receive antennas, even at finite Signal-to-Noise Ratio (SNR). Thus, although the capacity of the fading dirty paper channel remains unknown, this paper shows it is not far from its dirt-free counterpart. The insights from the dirty paper channel directly lead to transmission strategies for the two-user MIMO broadcast channel, where the transmitter emits a superposition of desired and undesired (dirt) signals with respect to each receiver. The performance of the lattice coding scheme is analyzed under different fading dynamics for the two users, showing that high-dimensional lattices achieve rates close to capacity. [ABSTRACT FROM PUBLISHER]

This paper studies the secure transmission in a multiuser broadcast channel where only the statistical channel state information of the eavesdropper is available. We propose to apply secret dirty-paper coding (S-DPC) in this scenario to support the secure transmission of one user and the normal (unclassified) transmission of the other users. By adopting the S-DPC and encoding the secret message in the first place, all the information-bearing signals of the normal transmission are treated as noise by potential eavesdroppers and thus provide secrecy for the secure transmission. In this way, the proposed approach exploits the intrinsic secrecy of multiuser broadcasting and can serve as an energy-efficient alternative to the traditional artificial noise (AN) scheme. To evaluate the secrecy performance of this approach and compare it with the AN scheme, we propose two S-DPC-based secure transmission schemes for maximizing the secrecy rate under constraints on the secrecy outage probability (SOP) and the normal transmission rates. The first scheme directly optimizes the covariance matrices of the transmit signals, and a novel approximation of the intractable SOP constraint is derived to facilitate the optimization. The second scheme combines zero-forcing dirty-paper coding and AN, and the optimization involves only power allocation. We establish efficient numerical algorithms to solve the optimization problems for both schemes. Theoretical and simulation results confirm that, in addition to supporting the normal transmission, the achievable secrecy rates of the proposed schemes can be close to that of the traditional AN scheme, which supports only the secure transmission of one user. [ABSTRACT FROM PUBLISHER]

We introduce a fundamental lemma called the Poisson matching lemma, and apply it to prove one-shot achievability results for various settings, namely channels with state information at the encoder, lossy source coding with side information at the decoder, joint source-channel coding, broadcast channels, distributed lossy source coding, multiple access channels and channel resolvability. Our one-shot bounds improve upon the best known one-shot bounds in most of the aforementioned settings (except multiple access channels and channel resolvability, where we recover bounds comparable to the best known bounds), with shorter proofs in some settings even when compared to the conventional asymptotic approach using typicality. The Poisson matching lemma replaces both the packing and covering lemmas, greatly simplifying the error analysis. This paper extends the work of Li and El Gamal on Poisson functional representation, which mainly considered variable-length source coding settings, whereas this paper studies fixed-length settings, and is not limited to source coding, showing that the Poisson functional representation is a viable alternative to typicality for most problems in network information theory. [ABSTRACT FROM AUTHOR]

A memoryless bivariate Gaussian source is transmitted to a pair of receivers over an average-power limited bandwidth-matched Gaussian broadcast channel. Based on their observations, Receiver 1 reconstructs the first source component while Receiver 2 reconstructs the second source component both seeking to minimize the expected squared-error distortions. In addition to the source transmission digital information at a specified rate should be conveyed reliably to Receiver 1–the “stronger” receiver. Given the message rate we characterize the achievable distortions region. Specifically, there is an ${\sf SNR}$ -threshold below which Dirty Paper coding of the digital information against a linear combination of the source components is optimal. The threshold is a function of the digital information rate, the source correlation and the distortion at the “stronger” receiver. Above this threshold a Dirty Paper coding extension of the Tian-Diggavi-Shamai hybrid scheme is shown to be optimal. [ABSTRACT FROM AUTHOR]

The expected development of the future generation of wireless communications systems such as 6G aims to achieve an ultrareliable and low-latency communications (URLLCs) while maximizing the data rates. These requirements push research into developing new advanced technologies. To this end, massive multiple input multiple output (MMIMO) is introduced as a promising transmission approach to fulfill these requirements. However, maximizing the downlink-achievable sum rate (DASR) in MMIMO with a frequency division duplex (FDD) transmission mode and limited coherence time (LCT) is very challenging. To address this challenge, this paper proposes a DASR maximization approach using a feasible power allocation optimization method. The proposed approach is based on smartly allocating the total transmit power between the data transmission and training sequence transmission for channel estimation. This can be achieved by allocating more energy to the training signal than the data transmission during the channel estimation process to improve the quality of channel estimation without compromising more training sequence length, thus maximizing the DASR. Additionally, the theory of random matrix approach is exploited to derive an asymptotic closed-form expression for the DASR with a regularized zero-forcing precoder (RZFP), which allows the power optimization process to be achieved without the need for computationally complex Monte Carlo simulations. The results provided in this paper indicate that a considerable enhancement in the DASR performance is achieved using the proposed power allocation method in comparison with the conventional uniform power allocation method. [ABSTRACT FROM AUTHOR]

Bluetooth Low Energy Mesh (BLE Mesh) enables Bluetooth flexibility and coverage by introducing Low-Power Nodes (LPNs) and enhanced networking protocol. It is also a commonly used communication method in sensor networks. In BLE Mesh, LPNs are periodically woken to exchange messages in a stop-and-wait way, where the tradeoff between energy and efficiency is a hard problem. Related works have reduced the energy consumption of LPNs mainly in the direction of changing the bearer layer, improving time synchronization and broadcast channel utilization. These algorithms improve communication efficiency; however, they cause energy loss, especially for the LPNs. In this paper, we propose a constrained flooding algorithm based on time series prediction and lightweight GBN (Go-Back-N). On the one hand, the wake-up cycle of the LPNs is determined by the time series prediction of the surrounding load. On the other, LPNs exchange messages through lightweight GBN, which improves the window and ACK mechanisms. Simulation results validate the effectiveness of the Time series Prediction and LlightWeight GBN (TP-LW) algorithm in energy consumption and throughput. Compared with the original algorithm of BLE Mesh, when fewer packets are transmitted, the throughput is increased by 214.71%, and the energy consumption is reduced by 65.14%. [ABSTRACT FROM AUTHOR]

In this paper, the effects of energy harvesting (EH) on an automatic repeat request based cooperative communication network comprised of a source, a relay, and two destination nodes, are investigated in Rayleigh fading channels. The energy of the decode-and-forward relay is provided by EH throughout the radio frequency signal from the source. In the proposed transmission protocol, the source transmits a data packet to the relay and two destination nodes by direct links. If the transmission is successful at both destination nodes, these nodes reply by an acknowledgement (ACK) signal to the source and the relay. Otherwise, there are two alternatives: If the relay has received this data packet successfully and replied by an ACK signal, then it cooperates and transmits the data packet for a second time to two destination nodes. If the relay has failed and replied by a non-acknowledgement signal, the source in this case retransmits this packet to the destination nodes by direct links. First, a broadcast channel is considered where the source transmits the same data packet to the relay and destination nodes. Second, the non-orthogonal multiple access technique is applied to the same network where different packets are sent to each destination node by means of superposition coding. In both cases, the system throughputs are obtained from the derived closed-form expressions for the outage probabilities based on the Markov chain model. All theoretical results are supported by computer simulation results. [ABSTRACT FROM AUTHOR]

In this paper, we want to investigate classical-quantum multiple access wiretap channels (CQ-MA-WTC) under one-shot setting. In this regard, we analyze the CQ-MA-WTC using a simultaneous position-based decoder for reliable decoding and using a newly introduced technique to decode securely. Also, for the sake of comparison, we analyze the CQ-MA-WTC using Sen's one-shot joint typicality lemma for reliable decoding. The simultaneous position-based decoder tends to a multiple hypothesis testing problem. Also, using convex splitting to analyze the privacy criteria in a simultaneous scenario becomes problematic. To overcome both problems, we first introduce a new channel that can be considered as a dual to the CQ-MA-WTC. This channel is called a point-to-point quantum wiretap channel with multiple messages (PP-QWTC). In the following, as a strategy to solve the problem, we also investigate and analyze quantum broadcast channels (QBC) in the one-shot regime. [ABSTRACT FROM AUTHOR]

This paper derives the maximum achievable sum-rate and presents the optimal encoding/decoding framework for rate-diverse wireless network coding (RD-WNC) over broadband channels consisting of multiple parallel subchannels. RD-WNC applies to a communication scenario in which a base station wants to deliver two different messages with different rates to two users. The base station combines the two separate messages into one network-coded message and broadcasts the network-coded message to both users. Each user then extracts its desired message from the network-coded message by subtracting from it the other message, which we assume to be side information available to the user. Deriving the maximum achievable sum-rate for RD-WNC is challenging when the channel consists of multiple parallel subchannels with different channel coefficients (e.g., the subcarrier channels of OFDM systems), since apart from the rate allocation between the two users, optimal power allocation among multiple subchannels needs to be identified. The first contribution of this paper is a new “mountain-leveling” power allocation algorithm to achieve the maximum sum-rate. With the resulting power allocation, we can then achieve the corresponding optimal sum-rate by having a separate encoding/decoding mechanism for each subchannels, but doing so is cumbersome and complex when the number of subchannels is large. The second contribution of this paper is a practical encoding/decoding framework using only one encoder-decoder mechanism for all subchannels without sacrificing sum-rate optimality. We provide numerical results to corroborate our theoretical findings and to demonstrate the benefits of our encoding/decoding framework. [ABSTRACT FROM AUTHOR]

In wireless networks, the link connectivity may be intermittent due to shadowing, burstiness of data arrival, or uncoordinated resource allocation. In this paper, we model the intermittence of links as Bernoulli distributed random channel states, termed intermittence channel states, and study the impact of the corresponding channel state information at the transmitter (CSIT) in a two-user Gaussian broadcast channel (BC). Moreover, due to the heterogeneous timeliness of intermittence channel states, the CSIT considered in this paper is hybrid. More specifically, the CSIT of each link can be perfectly (causally or non-causally) available, delayed, or not available. When the links are connected, we adopt a general setting that the received signal-to-noise ratios can be different. Our contribution is the characterization of the capacity regions of intermittent Gaussian BC to within bounded gaps for all combinations of hybrid CSIT, except for scenario DN (delayed CSIT of receiver 1, no CSIT of receiver 2). For scenario DN, we propose an opportunistic physical layer network coding scheme that achieves a strictly larger degree-of-freedom (DoF) region than the no-CSIT DoF region. As a corollary, single-user CSIT is able to increase the sum DoF for intermittent Gaussian BC (also the capacity region for the erasure BC, as a by-product). This result is in sharp contrast to the recent negative result by Davoodi and Jafar, where it is shown that for fast-fading multiple-input single-output BC with continuous channel states, single-user CSIT does not help at all in terms of sum DoF. [ABSTRACT FROM AUTHOR]

In wireless communication systems, channel state feedback (CSF) is widely used to improve link performance. However, CSF consumes extra system resources and results in transmission overhead. In this paper, we evaluate such resource consumption in terms of bit rate and provide an explicit expression for the lower bound of the CSF overhead. We propose an overhead optimization mechanism under the constraint of channel state reconstruction accuracy. The numerical simulations show that our paper is beneficial to select the optimum CSF parameters, including the average bit number and channel state feedback period. It is also shown that the proposed overhead optimization scheme is able to reduce the system resource consumption with a guaranteed reconstruction accuracy. [ABSTRACT FROM AUTHOR]

In a wireless ad hoc network, nodes share a broadcast channel through a Medium Access Control protocol. The broadcasting channel is a scarce resource, so MAC algorithms must reduce collisions and ensure high network throughput. The IEEE 802.11 MAC protocol used in ad hoc networks can lead to unfairness in channel utilization among flows, some nodes may grab the channel for a long time and deprive the other nodes of accessing the channel. In this paper, a new approach to make the Medium Access Control in wireless ad hoc networks more efficient and fairer is proposed. This approach is based on a service differentiation between the nodes of the network by taking into account, for each node, the number of its outgoing flows. The principle of this approach is to give a node a bandwidth that must be proportional to the number of its outgoing flows. In that way, if a node has more outgoing flows than another or is more involved in routing than another it will have a high priority to access the channel. As a consequence of this approach, the network won't break down because of the cooperation of all the nodes of the network, and bandwidth sharing will be fairer and more efficient. [ABSTRACT FROM AUTHOR]

Information-theoretic analysis of the communication systems performances is of practical and theoretical importance. In this paper, (i) Specifically, we generalize the Cover–Chiang work on point to point channel with two-sided state information to two-receiver less noisy broadcast channel (2R-LN-BC) with different side information non-causally known at the encoder as well as the decoders, and obtain the capacity region including the previous works as its special cases. Then, (ii) the obtained result is expanded to the continuous alphabet Gaussian version. In this Gaussian version, the side information available at the receivers are supposed to be correlated on the channel noises and the impact of these receivers cognition of the noises on the capacity region is analyzed. [ABSTRACT FROM AUTHOR]

In this paper, a new two-phase-feedback-based user-scheduling-and-beamforming method is proposed for multi-user multiple-input multiple-output downlink in the context of two-stage beamforming. The key ideas of the proposed method are: 1) to use a set of orthogonal reference beams and construct a cone around each reference beam to select “nearly-optimal” semi-orthogonal users based only on channel quality indicator feedback; and 2) to apply post-user-selection beam design with zero-forcing beamforming (ZFBF) based on channel state information (CSI) feedback only from the selected users. It is proven that the proposed scheduling-and-beamforming method is asymptotically optimal as the number of users increase. Furthermore, the proposed scheduling-and-beamforming method almost achieves the performance of the existing semi-orthogonal user selection with ZFBF that requires full CSI for all users, with a significantly reduced amount of required channel information which is even less than that required by random beamforming. [ABSTRACT FROM PUBLISHER]

Uplink-downlink duality refers to the fact that under a sum-power constraint, the capacity regions of a Gaussian multiple-access channel and a Gaussian broadcast channel with Hermitian transposed channel matrices are identical. This paper generalizes this result to a cooperative cellular network, in which remote access-points are deployed as relays in serving the users under the coordination of a central processor (CP). In this model, the users and the relays are connected over noisy wireless links, while the relays and the CP are connected over noiseless but rate-limited fronthaul links. Based on a Lagrangian technique, this paper establishes a duality relationship between such a multiple-access relay channel and broadcast relay channel, under the assumption that the relays use compression-based strategies. Specifically, we show that under the same total transmit power constraint and individual fronthaul rate constraints, the achievable rate regions of the Gaussian multiple-access and broadcast relay channels are identical, when either independent compression or Wyner-Ziv and multivariate compression strategies are used. The key observations are that if the beamforming vectors at the relays are fixed, the sum-power minimization problems under the achievable rate and fronthaul constraints in both the uplink and the downlink can be transformed into either a linear programming or a semidefinite programming problem depending on the compression technique, and that the uplink and downlink problems are Lagrangian duals of each other. Moreover, the dual variables corresponding to the downlink rate constraints become the uplink powers; the dual variables corresponding to the downlink fronthaul constraints become the uplink quantization noises. This duality relationship enables an efficient algorithm for optimizing the downlink transmission and relaying strategies based on the uplink. [ABSTRACT FROM AUTHOR]

This paper derives upper and lower bounds on the secrecy capacity-memory tradeoff of a wiretap erasure broadcast channel (BC) with ${\mathsf{K}}_{w} $ weak receivers and ${\mathsf {K}}_{s} $ strong receivers, where weak receivers and strong receivers have the same erasure probabilities and cache sizes, respectively. The lower bounds are achieved by the schemes that meticulously combine joint cache-channel coding with wiretap coding and key-aided one-time pads. The presented upper bound holds more generally for arbitrary degraded BCs and arbitrary cache sizes. When only weak receivers have cache memories, upper and lower bounds coincide for small and large cache memories, thus providing the exact secrecy capacity-memory tradeoff for this setup. The derived bounds further allow us to conclude that the secrecy capacity is positive even when the eavesdropper is stronger than all the legitimate receivers with cache memories. Moreover, they show that the secrecy capacity-memory tradeoff can be significantly smaller than its non-secure counterpart, but it grows much faster when cache memories are small. This paper also presents a lower bound on the global secrecy capacity-memory tradeoff where one is allowed to optimize the cache assignment subject to a total cache budget. It is close to the best known lower bound without secrecy constraint. For small total cache budget, the global secrecy capacity-memory tradeoff is achieved by assigning all the available cache memory uniformly over all the receivers if the eavesdropper is stronger than all the legitimate receivers, and it is achieved by assigning the cache memory uniformly only over the weak receivers if the eavesdropper is weaker than the strong receivers. [ABSTRACT FROM AUTHOR]

In this paper, we propose an interference alignment (IA) scheme for the multiple-input multiple-output (MIMO) uplink cellular network with the help of a relay which operates in half-duplex mode. The proposed scheme only requires global channel state information (CSI) knowledge at the relay, with no transmitter beamforming and time extension at the user equipment (UE), which differs from conventional IA schemes for cellular networks. We derive the feasibility condition of the proposed scheme for the general cellular network configuration and analyze the degrees-of-freedom (DoF) performance of the proposed IA scheme while providing a closed-form beamformer design at the relay. Extensions of the proposed scheme to downlink and full-duplex cellular networks are also proposed in this paper. The DoF performance of the proposed scheme is compared to those of linear IA scheme and relay-aided interference management scheme for a cellular network with no time extension. It is also shown that advantages similar to those in the uplink case can be obtained for the downlink case through the duality of a relay-aided interfering multiple-access channel (IMAC) and an interfering broadcast channel (IBC). Furthermore, the proposed scheme for a full-duplex cellular network is shown to have advantages identical to those of a number of proposed half-duplex cellular cases. [ABSTRACT FROM AUTHOR]

Linear coding schemes have been the main choice of coding for the additive white Gaussian noise broadcast channel (AWGN-BC) with noiseless feedback in the literature. The achievable rate regions of these schemes go well beyond the capacity region of the AWGN-BC without feedback. In this paper, a concatenated coding design for the $K$-user AWGN-BC with noisy feedback is proposed that relies on linear schemes as inner codes to achieve rate tuples outside the no-feedback capacity region. The boundary of an achievable rate region of purely linear coding schemes for noiseless feedback is shown to be arbitrarily closely approached by the concatenated coding scheme for sufficiently small feedback noise levels. Then, a linear coding scheme for the $K$-user symmetric AWGN-BC with noisy feedback is presented and optimized for use in the concatenated coding scheme. For noiseless feedback, the presented linear coding scheme achieves the optimal sum-rate of linear-feedback coding. An upper bound on the inner code blocklength needed to achieve a sum-rate above no-feedback sum-capacity is derived. [ABSTRACT FROM PUBLISHER]

This paper studies a multiple-input–single-output (MISO) broadcast channel (BC) featuring simultaneous wireless information and power transfer, where a multiantenna access point (AP) delivers both information and energy via radio signals to multiple single-antenna receivers simultaneously, and each receiver implements either information decoding (ID) or energy harvesting (EH). In particular, pseudorandom sequences that are a priori known and therefore can be cancelled at each ID receiver are used as the energy signals, and the information-theoretically optimal dirty paper coding is employed for the information transmission. We characterize the capacity region for ID receivers by solving a sequence of weighted sum-rate (WSR) maximization (WSRMax) problems subject to a maximum sum-power constraint for the AP, and a set of minimum harvested power constraints for individual EH receivers. The problem corresponds to a new form of WSRMax problem in MISO-BC with combined maximum and minimum linear transmit covariance constraints (MaxLTCCs and MinLTCCs), which differs from the celebrated capacity region characterization problem for MISO-BC under a set of MaxLTCCs only and is challenging to solve. By extending the general BC–multiple-access-channel duality, which is only applicable to WSRMax problems with MaxLTCCs, and applying the ellipsoid method, we propose an efficient iterative algorithm to solve this problem globally optimally. Furthermore, we also propose two suboptimal algorithms with lower complexity by assuming that the information and energy signals are designed separately. Finally, numerical results are provided to validate our proposed algorithms. [ABSTRACT FROM PUBLISHER]

This paper studies lossy transmission of a memoryless bivariate Gaussian source over a bandwidth-mismatched memoryless Gaussian broadcast channel with two receivers, where each receiver is interested in reconstructing only one source component. For both bandwidth expansion and compression regimes, novel hybrid digital/analog (HDA) coding schemes are proposed. With appropriate choice of parameters, our schemes are shown to specialize to separate source–channel coding studied by Gao and Tuncel, and is, therefore, superior to it in both bandwidth regimes. Our scheme for bandwidth expansion also outperforms the HDA coding scheme of Behroozi et al. On the other hand, if a proposed conjecture (supported by numerical observations) is indeed true, the same superiority follows for the bandwidth compression regime as well. Finally, when the bandwidth expansion/compression ratio approaches 1, both of our schemes become optimal as their performance approaches that of the bandwidth-matched scheme of Tian et al. [ABSTRACT FROM PUBLISHER]

This paper aims to characterize the capacity limits of a wireless cellular network with a full-duplex (FD) base-station (BS) and half-duplex user terminals, in which three independent messages are communicated: the uplink message m1 from the uplink user to the BS, the downlink message m2 from the BS to the downlink user, and the device-to-device (D2D) message m3 from the uplink user to the downlink user. From an information theoretical perspective, the overall network can be viewed as a generalization of the FD relay broadcast channel with a side message transmitted from the relay to the destination. We begin with a simpler case that involves the uplink and downlink transmissions of (m1, m2) only, and propose an achievable rate region based on a novel strategy that uses the BS as a FD relay to facilitate the interference cancellation at the downlink user. We also prove a new converse, which is strictly tighter than the cut-set bound, and characterize the capacity region of the scalar Gaussian FD network without a D2D message to within a constant gap. This paper further studies a general setup wherein (m1, m2, m3) are communicated simultaneously. To account for the D2D message, we incorporate Marton’s broadcast coding into the previous scheme to obtain a larger achievable rate region than the existing ones in the literature. We also improve the cut-set bound by means of genie and show that by using one of the two simple rate-splitting schemes, the capacity region of the scalar Gaussian FD network with a D2D message can already be reached to within a constant gap. Finally, a generalization to the vector Gaussian channel case is discussed. Simulation results demonstrate the advantage of using the BS as relay in enhancing the throughput of the FD cellular network. [ABSTRACT FROM AUTHOR]

THIS PAPER EXPLORES HOW REVISIONIST AUTOCRATIC GOVERNMENTS USE GLOBAL BROADCASTING NEWS CHANNELS TO COUNTER THE SO-CALLED WESTERN HEGEMONY NARRATIVE. IT FOCUSES ON HOW AND WHY THE SPANISH-SPEAKING WORLD WAS TARGETED BY INTERNATIONAL BROADCASTERS FOUNDED BY AUTOCRATIC AND REVISIONIST GOVERNMENTS AND HOW THE WAR WAGED BY THE RUSSIAN FEDERATION AGAINST UKRAINE IS PRESENTED IN THREE SO-CALLED 'ANTI-HEGEMONY' MEDIA NETWORKS: CHINA GLOBAL TELEVISION NETWORK EN ESPAÑOL (CGTN), TELESUR AND HISPAN TV. BY USING QUALITATIVE RESEARCH METHODS SUCH AS CONTENT ANALYSIS AND CHRONOLOGICAL ANALYSIS OF NEWS COVERING THE RUSSIAN INVASION OF UKRAINE PRESENTED BY TELESUR, HISPAN TV AND CGTN IN SPANISH SINCE 24 FEBRUARY 2022, THIS PAPER ARGUES THAT ALL THREE MEDIA CHANNELS PROMOTE IN DIFFERENT SHADES A KREMLIN-BASED NARRATIVE. THE ARTICLE FURTHER DEBATES THE PROFOUND FOREIGN POLICY IMPLICATIONS OF THIS TACIT MEDIA ALLIANCE AND SUPPORTS THE CONCLUSION THAT THE CURRENT WAR WAGED BY RUSSIA IN UKRAINE IS USED IN DIFFERENT WAYS BY REVISIONIST AND ASSERTIVE GOVERNMENTS TO PROMOTE THEIR OWN REVISIONIST AGENDAS BOTH DOMESTICALLY AND ABROAD. [ABSTRACT FROM AUTHOR]

In this paper, we consider a status updating system where updates are generated at a constant rate at $K$ sources and sent to the corresponding recipients through a noise-free broadcast channel. We assume that perfect channel state information (CSI) is available at the transmitter before each transmission, and the transmitter is able to utilize the CSI to precode the updates. Our object is to design optimal precoding schemes to minimize the summed average age of information (AoI) at the recipients. Under various assumptions on the size of each update $B$ , the number of transmit antennas $M$ , and the number of receive antennas $N$ at each user, this paper identifies the corresponding age-optimal precoding and transmission scheduling strategies. Specifically, for the case when $N=1$ , a round-robin based updating scheme is shown to be optimal. For the two-user systems with $N>B$ or $M\notin [N:2N]$ , framed updating schemes are proven to be optimal. For other cases in the two-user systems, a framed alternating updating scheme is proven to be 2-optimal. [ABSTRACT FROM AUTHOR]

One of the key challenges for future communication systems is to deal with fast changing channels due to the mobility of users. Having a robust protocol capable of handling transmission failures in unfavorable channel conditions is crucial, but the feedback capacity may be greatly limited due to strict latency requirements. This paper studies the hybrid automatic repeat request (HARQ) techniques involved in re-transmissions when decoding failures occur at the receiver and proposes a scheme that relies on codeword bundling and adaptive incremental redundancy (IR) to maximize the overall throughput in a limited feedback system. In addition to the traditional codeword extension IR bits, this paper introduces a new type of IR, bundle parity bits, obtained from an erasure code across all the codewords in a bundle. The type and number of IR bits to be sent as a response to a decoding failure is optimized through a Markov Decision Process. In addition to the single link analysis, the paper studies how the same techniques generalize to relay and multi-user broadcast systems. Simulation results show that the proposed schemes can provide a significant increase in throughput over traditional HARQ techniques. [ABSTRACT FROM AUTHOR]

In the field of satellite data broadcasting, the management quality of data broadcasting bandwidth is directly related to the throughput of the broadcasting system and plays an important role in the performance of satellites. In this paper, for the sun-synchronous orbit meteorological satellite broadcasting which has the conventional product files and emergency information, a broadcast bandwidth statistical multiplexing and control method is designed for bandwidth management. It can be used for the management of broadcasting between regular products and emergency information, as well as internal broadcasting among regular products. This paper is the first to apply common multiplexing of PID and channel mode (CMPCM) to satellite broadcasting. The test verified that the broadcast channel of the parameters and the broadcast schedule management channel resources achieved statistical multiplexing of bandwidth, ratio of channel management functions, and data broadcast control. Broadcasting occupation ratio (BOR) and broadcasting file error ratio (BER) improved significantly. This is significant for improving the efficiency of satellite uplink broadcasting. [ABSTRACT FROM AUTHOR]

Caching is an efficient way to reduce network traffic congestion during peak hours, by storing some content at the user’s local cache memory, even without knowledge of user’s later demands. Maddah-Ali and Niesen proposed a two-phase (placement phase and delivery phase) coded caching strategy for broadcast channels with cache-aided users. This paper investigates the same model under the constraint that content is placed uncoded within the caches, that is, when bits of the files are simply copied within the caches. When the cache contents are uncoded and the users’ demands are revealed, the caching problem can be connected to an index coding problem. This paper focuses on deriving fundamental performance limits for the caching problem by using tools for the index coding problem that were either known or are newly developed in this work. First, a converse bound for the caching problem under the constraint of uncoded cache placement is proposed based on the “acyclic index coding converse bound.” This converse bound is proved to be achievable by the Maddah-Ali and Niesen’s scheme when the number of files is not less than the number of users, and by a newly derived index coding achievable scheme otherwise. The proposed index coding achievable scheme is based on distributed source coding and strictly improves on the widely used “composite (index) coding” achievable bound and its improvements, and is of independent interest. An important consequence of the findings of this paper is that advancements on the coded caching problem posed by Maddah-Ali and Niesen are thus only possible by considering strategies with coded placement phase. A recent work by Yu et al has however shown that coded cache placement can at most half the network load compared to the results presented in this paper. [ABSTRACT FROM AUTHOR]

This paper considers a state dependent broadcast channel with one transmitter, Alice, and two receivers, Bob and Eve. The problem is to effectively convey (“amplify”) the channel state sequence to Bob while “masking” it from Eve. The extent to which the state sequence cannot be masked from Eve is referred to as leakage. This can be viewed as a secrecy problem, where we desire that the channel state itself be minimally leaked to Eve while being communicated to Bob. This paper is aimed at characterizing the tradeoff region between amplification and leakage rates for such a system. An achievable coding scheme is presented, wherein the transmitter transmits a partial state information over the channel to facilitate the amplification process. For the case when Bob observes a stronger signal than Eve, the achievable coding scheme is enhanced with secure refinement. Outer bounds on the tradeoff region are also derived, and used in characterizing some special case results. In particular, the optimal amplification-leakage rate difference, called as differential amplification capacity, is characterized for the reversely degraded discrete memoryless channel, the degraded binary, and the degraded Gaussian channels. In addition, for the degraded Gaussian model, the extremal corner points of the tradeoff region are characterized, and the gap between the outer bound and achievable rate-regions is shown to be less than half a bit for a wide set of channel parameters. [ABSTRACT FROM PUBLISHER]

This paper introduces Manhattan sampling in two and higher dimensions, and proves sampling theorems for them. In 2-D, Manhattan sampling, which takes samples densely along a Manhattan grid of lines, can be viewed as sampling on the union of two rectangular lattices, one dense horizontally and the other vertically, with the coarse spacing of each being a multiple of the fine spacing of the other. The sampling theorem shows that the images bandlimited to the union of the Nyquist regions of the two rectangular lattices can be recovered from their Manhattan samples, and an efficient procedure for doing so is given. Such recovery is possible even though there is an overlap among the spectral replicas induced by Manhattan sampling. In three and higher dimensions, there are many possible configurations for Manhattan sampling, each consisting of the union of special rectangular lattices called bi-step lattices. This paper identifies them, proves a sampling theorem showing that the images bandlimited to the union of the Nyquist regions of the bi-step rectangular lattices are recoverable from Manhattan samples, presents an efficient onion-peeling procedure for doing so, and shows that the union of Nyquist regions is as large as any bandlimited region, such that all images supported by such can be stably reconstructed from samples taken at the rate of the Manhattan sampling. It also develops a special representation for the bi-step lattices with a number of useful properties. While most of this paper deals with continuous-space images, Manhattan sampling of discrete-space images is also considered, for infinite, as well as finite, support images. [ABSTRACT FROM AUTHOR]

In this paper, we study a security problem on a simple wiretap network, consisting of a source node S, a destination node D, and an intermediate node R. The intermediate node connects the source and the destination nodes via a set of noiseless parallel channels, with sizes n1 and n2 , respectively. A message $M$ is to be sent from S to D. The information in the network may be eavesdropped by a set of wiretappers. The wiretappers cannot communicate with one another. Each wiretapper can access a subset of channels, called a wiretap set. All the chosen wiretap sets form a wiretap pattern. A random key $K$ is generated at S, and a coding scheme on $(M, K)$ is employed to protect $M$ . We define two decoding classes at D. In Class-I, only $M$ is required to be recovered, and in Class-II, both $M$ and $K$ are required to be recovered. The objective is to minimize $H(K)/H(M)$ for a given wiretap pattern under the perfect secrecy constraint. The first question we address is whether routing is optimal on this simple network. By enumerating all the wiretap patterns on the Class-I/II (3, 3) networks and harnessing the power of Shannon-type inequalities, we find that gaps exist between the bounds implied by routing and the bounds implied by Shannon-type inequalities for a small fraction (<2%) of all the wiretap patterns. The second question we investigate is the following: What is $\min H(K)/H(M)$ for the remaining wiretap patterns where gaps exist? We study some simple wiretap patterns and find that their Shannon bounds (i.e., the lower bound induced by Shannon-type inequalities) can be achieved by linear codes, which means routing is not sufficient even for the (3, 3) network. For some complicated wiretap patterns, we study the structures of linear coding schemes under the assumption that they can achieve the corresponding Shannon bounds. This paper indicates that the determination of the entropic region of six linear vector spaces cannot be sidestepped. Some subtle issues on the network models are discussed, and interesting observations are stated. [ABSTRACT FROM AUTHOR]

Consider a Gaussian multiple-input multiple-output (MIMO) multiple-access channel (MAC) with channel matrix \mathbf H and a Gaussian MIMO broadcast channel (BC) with channel matrix \mathbf H ^\mathsf T . For the MIMO MAC, the integer-forcing architecture consists of first decoding integer-linear combinations of the transmitted codewords, which are then solved for the original messages. For the MIMO BC, the integer-forcing architecture consists of pre-inverting the integer-linear combinations at the transmitter, so that each receiver can obtain its desired codeword by decoding an integer-linear combination. In both the cases, integer-forcing offers higher achievable rates than zero-forcing while maintaining a similar implementation complexity. This paper establishes an uplink-downlink duality relationship for integer-forcing, i.e., any sum rate that is achievable via integer-forcing on the MIMO MAC can be achieved via integer-forcing on the MIMO BC with the same sum power and vice versa. Using this duality relationship, it is shown that integer-forcing can operate within a constant gap of the MIMO BC sum capacity. Finally, the paper proposes a duality-based iterative algorithm for the non-convex problem of selecting optimal beamforming and equalization vectors, and establishes that it converges to a local optimum. [ABSTRACT FROM PUBLISHER]

With the explosive proliferation of connected devices and mobile users in the Internet-of-things, multiple access techniques are urged to be developed for the next generation wireless communications. Recently, rate-splitting multiple access (RSMA) has been a promising communication technology that holds advantages of strong robustness, low complexity, and high spectral efficiency, which can be integrated with the indoor visible light communication (VLC) broadcast system to compensate for the shortcomings of limited modulation bandwidth of LEDs. However, the research on the RSMA-based VLC systems is still in its infancy and there exist various problems to be explored. To benefit from the RSMA technique, this paper investigates the energy efficiency optimizations for both single-cell and multi-cell RSMA-based VLC broadcast systems. Specifically, these two systems are modeled, where the VLC broadcast channel follows Lambertian radiation model, and the splitting design and successive interference cancellation of RSMA are employed to mitigate the multi-user interference. Especially for multi-cell networks, the zero-forcing approach is adopted to eliminate the inter-cell interference. To maximize the energy efficiency, the precoding and power allocation problems are formulated for single-cell and multi-cell networks while accommodating multiple constraints including dynamic operation ranges of LEDs, QoS requirements, and interference elimination. For solving these non-convex fractional problems, two pieces of successive convex approximation (SCA)-based algorithms are proposed, in which the variable transformation and linear approximation are adopted. Simulation results indicate that the proposed schemes can achieve superior energy efficiency with fast convergence for various network loads and user deployments. [ABSTRACT FROM AUTHOR]

In this paper, the Half-Duplex Relay Channel (HDRC) is thoroughly investigated. Even though this channel model is widely studied, the capacity is not yet fully understood and particularly has not been tightly expressed. In this work, a new capacity expression of the discrete memoryless HDRC is explicitly established. In particular, a new expression of the achievable rate is derived by taking advantage of the well-known capacity results of both the degraded broadcast channel and the multiple access channel. Specifi- cally, in order to obtain the achievable rate, the transmission from the source to destination is operated over two phases. In the first phase, the broadcast phase, the source broadcasts to both relay and destination. In the second phase, both source and relay transmit to destination to form multiple access channel. Then, we prove that the new achievable rate meets the cut-set outer bound such that the capacity of the discrete memoryless HDRC is attained. Next, the new derived capacity result is extended to the case of additive Gaussian channel. Further, the attained capacity is analytically and then numerically shown to encompass all well-known available findings in the literature. Additional numerical examples are also shown to present the cases in which the relay is beneficial and how the achievable capacity varies with the source-relay and relay-destination channel gains. [ABSTRACT FROM AUTHOR]

In this paper, we investigate joint retrospective interference alignment (RIA) and caching schemes for multiple-input single-output (MISO) broadcast channels (BC) with delayed channel state information at the transmitter (CSIT). By exploiting the cached content, we propose one sophisticated cache-aided RIA scheme to cancel the interference. Importantly, our scheme takes the number of symbols in a packet into account, as different number of symbols in a packet result in different system configuration, which may have significant impact on the design of the transmission scheme and achievable degrees of freedom (DoF). Furthermore, we present two theorems to quantify the achievable sum DoF of the proposed cached-aided RIA scheme for different system configuration. Moreover, the system configuration of the existing cache-aided RIA scheme with mixed CSIT can be treated as a special case in our paper. And also our scheme can simultaneously support more users than the existing cache-aided RIA scheme with mixed CSIT to invoke zero forcing (ZF) precoding, which limits the number of users simultaneously supported. [ABSTRACT FROM AUTHOR]

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Characterizing the fundamental energy efficiency (EE) performance of multiple-input–multiple-output interfering broadcast channels (MIMO-IFBC) is important for the design of green wireless system. In this paper, we propose a new network architecture proposition based on EE maximization for Multi-Cell MIMO-IFBC within the context of interference alignment (IA). Particularly, EE is maximized subject to maximum power and minimum throughput constraints. We propose two schemes to optimize EE for different signal-to-noise ratio (SNR) regions. For high-SNR operating regions, we employ a grouping-based IA scheme to jointly cancel intra- and inter-cell interferences and thus transform the MIMO-IFBC to a single-cell MIMO scenario. A gradient-based power adaptation scheme is proposed based on water-filling power adaptation and singular value decomposition to maximize EE for each cell. For moderate SNR cases, we propose an approach using dirty paper coding (DPC) with the principle of multiple access channel and broadcast channel duality to perform IA while maximizing EE in each cell. The algorithm in its dual form is solved using a subgradient method and a bisection searching scheme. Simulation results demonstrate the superior performance of the proposed schemes over several existing approaches. It also shows that interference-nulling-based IA approaches outperform hybrid DPC-IA approach in high-SNR region, and the opposite occurs in low-SNR region. [ABSTRACT FROM PUBLISHER]

Studies of the MISO Broadcast Channel (BC) with delayed Channel State Information at the Transmitter (CSIT) have so far focused on the sum-rate and Degrees-of-Freedom (DoF) region analysis. In this paper, we investigate for the first time, the error rate performance at finite SNR and the diversity-multiplexing tradeoff (DMT) at infinite SNR of a space-time encoded transmission over a two-user MISO BC with delayed CSIT. We consider the so-called MAT protocol obtained by Maddah-Ali and Tse, which was shown to provide 33% DoF enhancement over TDMA. While the asymptotic DMT analysis shows that MAT is always preferable to TDMA, the Pairwise Error Probability analysis at finite SNR shows that MAT is in fact not always a better alternative to TDMA. Benefits can be obtained over TDMA only at a very high rate or once concatenated with a full-rate full-diversity space-time code. The analysis is also extended to spatially correlated channels, and the influence of transmit correlation matrices and user pairing strategies on the performance are discussed. Relying on statistical CSIT, signal constellations are further optimized to improve the error rate performance of MAT and make it insensitive to user orthogonality. Finally, other transmission strategies relying on delayed CSIT are discussed. [ABSTRACT FROM PUBLISHER]

In coding schemes for the wire-tap channel or for broadcast channels with confidential messages, it is well-known that the sender needs to use stochastic encoding to avoid information about the transmitted confidential message from being leaked to an eavesdropper. In this paper, we investigate the tradeoff between the rate of random numbers needed to realize the stochastic encoding and the rates of common, private, and confidential messages. For the direct theorem, we use the superposition coding scheme for the wire-tap channel, recently proposed by Chia and El Gamal, and its strong security is proved. The matching converse theorem is also established. Our result clarifies that a combination of ordinary stochastic encoding and channel prefixing by channel simulation is suboptimal. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the ergodic downlink sum-rate performance of a system consisting of a set of heterogeneous users. We study three user selection schemes to group near-orthogonal users for simultaneous transmission. The first scheme is a random selection policy that achieves fairness, but does not exploit multi-user diversity. The second scheme is a greedy selection policy that fully exploits multi-user diversity, but does not achieve fairness, and the third scheme achieves fairness while partially exploiting multi-user diversity. We also consider two beamforming methods for data transmission, namely, maximum-ratio transmission and zero-forcing beamforming. In all scheduling schemes studied in the paper, there is a key parameter that controls the degrees of orthogonality of channel directions between co-scheduled users. We focus on optimally setting this parameter for each scheduling scheme such that the ergodic downlink sum-rate is maximized. To this end, we derive analytical expressions for the ergodic downlink sum-rate considering each scheduling scheme. Numerical results are also presented to provide further insights. [ABSTRACT FROM PUBLISHER]

To address the exponentially rising demand for wireless content, the use of caching is emerging as a potential solution. It has been recently established that joint design of content delivery and storage (coded caching) can significantly improve performance over conventional caching. Coded caching is well suited to emerging heterogeneous wireless architectures which consist of a dense deployment of local-coverage wireless access points (APs) with high data rates, along with sparsely-distributed, large-coverage macro-cell base stations (BS). This enables design of coded caching-and-delivery schemes that equip APs with storage, and place content in them in a way that creates coded-multicast opportunities for combining with macro-cell broadcast to satisfy users even with different demands. Such coded-caching schemes have been shown to be order-optimal with respect to the BS transmission rate, for a system with single-level content, i.e., one where all content is uniformly popular. In this paper, we consider a system with non-uniform popularity content which is divided into multiple levels, based on varying degrees of popularity. The main contribution of this paper is the derivation of an order-optimal scheme which judiciously shares cache memory among files with different popularities. To show order-optimality we derive new information-theoretic lower bounds, which use a sliding-window entropy inequality, effectively creating a non-cut-set bound. We also extend the ideas to when users can access multiple caches along with the broadcast. Finally, we consider two extreme cases of user distribution across caches for the multi-level popularity model: a single user per cache (single-user setup) versus a large number of users per cache (multi-user setup), and demonstrate a dichotomy in the order-optimal strategies for these two extreme cases. [ABSTRACT FROM PUBLISHER]

Summary: In this paper, we consider the transmission over multiple access relay channel (MARC) in which the relay operates in half‐duplex mode. The main contribution of this paper is establishing the capacity of the multiple access half‐duplex relay channel (MAHRC). Toward achieving this goal, we first derive a new achievable rate region. While deriving the achievable rate region, well‐known encoding and decoding schemes, which are used for transmission and reception over the degraded broadcast channel and the multiple access channel, are used. In this transmission scheme, the transmission from the two sources via the half‐duplex relay, to the destination, is split into two phases. Afterwards, an outer bound to the transmission over the discrete memoryless MAHRC is developed. Consequently, we show that the achievable rate region matches the outer bound and therefore the capacity region is formed. Further, the capacity region is extended to the case of Gaussian channel. Additionally, many numerical examples are shown to validate our theoretical derivations. In particular, these numerical examples show that the achievable rate region, and then the capacity, that we derive is larger than the well‐known results in the literature. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is a new promising technology that is able to reconfigure the wireless propagation channel via smart and passive signal reflection. In this paper, we investigate the capacity region of a two-user communication network with one access point (AP) aided by $M$ IRS elements for enhancing the user-AP channels, where the IRS incurs negligible delay, thus the user-AP channels via the IRS follow the classic discrete memoryless channel model. In particular, we consider two practical IRS deployment strategies that lead to different effective channels between the users and AP, namely, the distributed deployment where the $M$ elements form two IRSs, each deployed in the vicinity of one user, versus the centralized deployment where all the $M$ elements are deployed in the vicinity of the AP. First, we consider the uplink multiple-access channel (MAC) and derive the capacity/achievable rate regions for both deployment strategies under different multiple access schemes. It is shown that the centralized deployment generally outperforms the distributed deployment under symmetric channel setups in terms of achievable user rates. Next, we extend the results to the downlink broadcast channel (BC) by leveraging the celebrated uplink-downlink (or MAC-BC) duality framework, and show that the superior rate performance of centralized over distributed deployment also holds. Numerical results are presented that validate our analysis, and reveal new and useful insights for optimal IRS deployment in wireless networks. [ABSTRACT FROM AUTHOR]

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This paper describes a process that integrates behavioral and decision science methods to design and evaluate interventions to disrupt illicit behaviors. We developed this process by extending a framework used to study systems with uncertain outcomes, where only partial information is observable, and wherein there are multiple participating parties with competing goals. The extended framework that we propose builds from artefactual data collection, thematic analysis, and descriptive analysis, toward predictive modeling and agent-based modeling. We use agent-based modeling to characterize and predict interactions between system participants for the purpose of improving our understanding of interventional targets in a virtual environment before piloting them in the field. We apply our extended framework to an exploratory case study that examines the potential of worker centers as a venue for deploying interventions to address labor exploitation and human trafficking. This case study focuses on reducing wage theft, the most prevalent form of exploitation experienced by day laborers and applies the first three steps of the extended framework. Specifically, the case study makes a preliminary assessment of two types of social interventions designed to disrupt exploitative processes and improve the experiences of day laborers, namely: (1) advocates training day laborers about their workers' rights and options that they have for addressing wage theft and (2) media campaigns designed to disseminate similar educational messages about workers' rights and options to address wage theft through broadcast channels. Applying the extended framework to this case study of day laborers at a worker center demonstrates how digital technology could be used to monitor, evaluate, and support collaborations between worker center staff and day laborers. Ideally, these collaborations could be improved to mitigate the risks and costs of wage theft, build trust between worker center stakeholders, and address communication challenges between day laborers and employers, in the context of temporary work. Based on the application of the extended framework to this case study of worker center day laborers, we discuss how next steps in the research framework should prioritize understanding how and why employers make decisions to participate in wage theft and the potential for restorative justice and equity matching as a relationship model for employers and laborers in a well-being economy. [ABSTRACT FROM AUTHOR]