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This paper proposes using the uncertainty of information (UoI), measured by Shannon’s entropy, as a metric for information freshness. We consider a system in which a central monitor observes M binary Markov processes through m communication channels (m

Software-defined Internet-of-Things networking (SDIoT) greatly simplifies the network monitoring in large-scale IoT networks by per-flow sampling, wherein the controller keeps track of all the active flows in the network and samples the IoT devices on each flow path to collect real-time flow statistics. There is a tradeoff between the controller’s sampling preference and the balancing of loads among devices. On the one hand, the controller may prefer to sample some of the IoT devices on the flow path because they yield more accurate flow statistics. On the other hand, it is desirable to sample the devices uniformly so that their energy consumptions and lifespan are balanced. This paper formulates the flow sampling problem in large-scale SDIoT networks by means of a Markov decision process and devises policies that strike a good balance between these two goals. Three classes of policies are investigated: the optimal policy, the state-independent policies, and the index policies (including the Whittle index and a second-order index policies). The second-order index policy is the most desired policy among all: 1) in terms of performance, it is on an equal footing with the Whittle index policy, and outperforms the state-independent policies by much; 2) in terms of complexity, it is much simpler than the optimal policy, and is comparable to state-independent policies and the Whittle index policy; 3) in terms of realizability, it requires no prior information on the network dynamics, hence is much easier to implement in practice. [ABSTRACT FROM AUTHOR]

Life-critical warning message, abbreviated as warning message, is a special event-driven message that carries emergency information in Vehicle-to-Everything (V2X). Three important characteristics that distinguish warning messages from ordinary vehicular messages are sporadicity, crowding, and ultra-time-criticality. Specifically, warning messages come only once in a while in a sporadic manner; however, when they come, they tend to come as a crowd and they need to be delivered in short order. This paper puts forth a medium-access control (MAC) protocol for warning messages. The overall MAC protocol operates by means of interrupt-and-access. To circumvent potential inefficiency arising from message sporadicity, we adopt an override network architecture whereby warning messages are delivered on the spectrum of the ordinary vehicular messages. A vehicle with a warning message first sends an interrupt signal to pre-empt the transmission of ordinary messages, so that the warning message can use the wireless spectrum originally allocated to ordinary messages. In this way, no exclusive spectrum resources need to be pre-allocated to the sporadic warning messages. Following the interrupt, for transmissions of ultra-time-critical crowd messages, we employ advanced channel access techniques to ensure reliable message delivery within an ultra-short time in the order of 10 ms. [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]

This paper explores the application of physical-layer network coding (PNC) for short-packet transmissions. PNC can potentially reduce the communication delay in relay-assisted wireless networks and can thus be instrumental in realizing short-packet communication systems with stringent delay requirements. In this work, first, we first derive an achievability bound for channel-coded short-packet PNC systems. Based on the random-coding error-exponent, the bound serves as a benchmark for short-packet PNC operating with traditional preamble-aided channel estimation and XOR channel decoding. Second, we design a blind channel estimation algorithm and a code-aided channel estimation algorithm for short-packet PNC systems. Both outperform the traditional preamble-aided channel estimation for PNC systems operating with mismatched channel-state-information. As a case study, we compare the three algorithms for packets of 128 symbols over a two-way relay channel. The results show that the blind algorithm outperforms the code-aided algorithm and preamble-aided algorithm by almost 0.2 and 1.5 dB respectively. Furthermore, the blind algorithm achieves the target packet error rate of 10−4 within 0.5 dB of the random coding bound of an imaginary system in which perfect channel-state-information is available at the relay at no cost (i.e., channel estimation is not required in the imaginary system). The bound and the algorithms give us a fundamental framework for applying PNC to short-packet transmissions. [ABSTRACT FROM AUTHOR]

This paper presents the results of a comprehensive investigation of complex linear physical-layer network coding (PNC) in two-way relay channels. In this system, two nodes A and B communicate with each other via a relay R. Nodes A and B send complex symbols, wA and wB , simultaneously to relay R. Based on the simultaneously received signals, relay R computes a linear combination of the symbols, wN=\alpha wA+\beta wB , as a network-coded symbol and then broadcasts wN to nodes A and B. Node A then obtains wB from wN and its self-information wA by wB=\beta ^{-1}(wN-\alpha wA) . Node B obtains wB in a similar way. A critical question at relay R is as follows: “given channel gain ratio \eta = hA/hB , where hA and hB are the complex channel gains from nodes A and B to relay R, respectively, what is the optimal coefficients (\alpha ,\beta ) that minimizes the symbol error rate (SER) of \alpha ,\beta ,w_{A}, w_{B} , and wN are the elements of a finite field of Gaussian integers, that is, the field of \mathbb {Z}[i]/q , where q is a Gaussian prime. Previous vector formulation, in which \alpha and \beta were represented by 2\times 2 matrices, corresponds to a subcase of our Gaussian-integer formulation, where q is real prime only. Extension to the Gaussian prime q , where q . We uncover the structure of the Voronoi regions that allows us to compute a minimum-distance metric that characterizes the SER of (\alpha \mathrm{ opt},\beta \mathrm{ opt}) . Overall, the contributions in 1) and 2) yield a toolset for a comprehensive understanding of complex linear PNC in \mathbb {Z}[i]/q . We believe investigation of linear PNC beyond \mathbb Z[i]/q can follow the same approach. [ABSTRACT FROM AUTHOR]

This paper proposes an encoding/decoding framework for achieving the optimal channel capacities of the two-user broadcast channel where each user (receiver) has the message targeted for the other user (receiver) as side information. Since the link qualities of the channels from the base station to the two users are different, their respective single-user non-broadcast channel capacities are also different. A goal is to simultaneously achieve/approach the single-user non-broadcast channel capacities of the two users with a single broadcast transmission by applying network coding. This is referred to as the rate-diverse wireless network coding problem. For this problem, this paper presents a capacity-achieving framework based on linear-structured nested lattice codes. The significance of the proposed framework, besides its theoretical optimality, is that it suggests a general design principle for linear rate-diverse wireless network coding going beyond the use of lattice codes. We refer to this design principle as the principle of virtual single-user channels. Guided by this design principle, we propose two implementations of our encoding/decoding framework using practical linear codes amenable to decoding with affordable complexities: the first implementation is based on Low Density Lattice Codes (LDLC) and the second implementation is based on Bit-interleaved Coded Modulation (BICM). These two implementations demonstrate the validity and performance advantage of our framework. [ABSTRACT FROM PUBLISHER]

Symbol misalignment is inevitable in asynchronous physical-layer network coding (PNC) systems. It is paramount that such symbol misalignment is taken into account in PNC decoding for good performance. Thus, accurate estimation of symbol misalignment is crucial. This paper argues that, when Nyquist pulses (i.e., intersymbol-interference (ISI)-free pulses) are adopted, signal samples only need to be collected at baud rate for optimal symbol misalignment estimation. Based on this principle, we propose a highly accurate symbol misalignment estimation method with low complexity. Our method makes use of the constant amplitude zero autocorrelation sequence (Zadoff–Chu sequence (ZC sequence)). We derive a maximum-likelihood (ML) estimator for symbol misalignment based on the cross-correlation result of the ZC sequence. Unlike previous methods that employ oversampling, our estimation method requires only baud-rate sampling, thus having much lower complexity. Extensive simulations show that our method can accurately estimate both integral and fractional symbol misalignments using sinc pulse and raised-cosine (RC) pulse. The root-mean-square error (RMSE) of the estimation is below 10−2 (in unit of symbol duration) when the SNR is above 15, 18, and 21 dB for 127-, 63-, and 31-bit-length ZC sequences, respectively. Furthermore, our method, being an ML estimation method, has no error floor in the high-SNR regime, whereas the prior methods exhibit an error floor. [ABSTRACT FROM PUBLISHER]

This paper presents several soft decision iterative decoding schemes for physical-layer network coding (PNC) operated with coded modulation (CM) and bit-interleaved coded modulation (BICM). With respect to PNC operated with CM, we consider network coding-based channel decoding (NC-CD) and multi-user complete decoding (MUD-NC) for PNC decoding at the relay. Their BICM counterparts are XOR-based channel decoding (XOR-CD) and MUD-XOR, respectively. First, we show that, when the decoding is non-iterative, there is a gap between the BICM capacities of both XOR-CD and MUD-XOR under Gray mapping and the capacities of their CM counterparts, NC-CD, and MUD-NC. This is in contrast to the conventional point-to-point communication system, for which the BICM capacity with Gray mapping is known to be very close to the CM capacity, without the need for iterative decoding. Second, we investigate the error performance of iteratively decoded BICM XOR-CD and MUD-XOR. Extrinsic information transfer chart analysis and simulation results indicate that for these Gray-mapped BICM PNC systems, iterative decoding can achieve considerable gains over non-iterative decoding. Again, this is in contrast to the Gray-mapped BICM point-to-point communication system, for which iterative decoding provides little gain over non-iterative decoding. We further show that Gray mapping gives rise to best PNC rate for MUD-XOR and XOR-CD systems among several bits-to-symbol mappings under study. Overall, our results indicate that BICM PNC systems exhibit different decoding behavior from conventional BICM point-to-point systems. This paper serves as a first foray into the investigation of this issue. [ABSTRACT FROM PUBLISHER]

This paper investigates a channel-coded multiuser system operated with orthogonal frequency-division multiplexing (OFDM) and interleaved-division multiple access (IDMA). In general, there are many variations to multiuser systems. Our choice of the combination of OFDM and IDMA is motivated by its ability to achieve multiuser diversity gain in frequency-selective multiple-access channels. To realize OFDM-IDMA, however, two challenges must be addressed. The first challenge is the estimation of multiple channel parameters, particularly how to contain the estimation errors of the channel parameters of the multiple users, considering that the overall estimation errors may increase with the number of users because the estimations of their channel parameters are intertwined with each other. The second challenge is that the transmitters of the multiple users may be driven by different radio-frequency oscillators. The associated frequency asynchrony may cause multiple carrier frequency offsets (CFOs) at the receiver. Compared with a single-user receiver where the single CFO can be compensated away at the receiver prior to channel decoding, a particular difficulty for a multiuser receiver is that it is not possible to compensate away all the multiple CFOs simultaneously. To tackle the two challenges, we put forth an integrated framework to solve the problems of multiuser channel-parameter estimation, CFO compensation, and channel decoding jointly and iteratively. The framework employs the space-alternating generalized expectation-maximization (SAGE) algorithm to decompose the multiuser problem into multiple single-user problems and the expectation-conditional maximization (ECM) algorithm to tackle each of the single-user subproblems. Iterative executions of SAGE and ECM in the framework allow the two aforementioned challenges to be tackled in an optimal manner. Simulation results indicate that, compared with other approaches, our approach can achieve significant bit-error-rate (BER) and mean-square-error (MSE) improvements. [ABSTRACT FROM PUBLISHER]

The growing demand for high-speed data, quality of service (QoS) assurance, and energy efficiency has triggered the evolution of fourth-generation (4G) Long-Term Evolution-Advanced (LTE-A) networks to fifth generation (5G) and beyond. Interference is still a major performance bottleneck. This paper studies the application of physical-layer network coding (PNC), which is a technique that exploits interference, in heterogeneous cellular networks. In particular, we propose a rate-maximizing relay selection algorithm for a single cell with multiple relays assuming the decode-and-forward (DF) strategy. With nodes transmitting at different powers, the proposed algorithm adapts the resource allocation according to the differing link rates, and we prove theoretically that the optimization problem is log-concave. The proposed technique is shown to perform significantly better than the widely studied selection-cooperation technique. We then undertake an experimental study—on a software radio platform—of the decoding performance of PNC with unbalanced signal-to-noise ratios (SNRs) in the multiple-access transmissions. This problem is inherent in cellular networks, and it is shown that, with channel coding and decoders based on multiuser detection and successive interference cancellation, the performance is better with power imbalance. This paper paves the way for further research on multicell PNC, resource allocation, and the implementation of PNC with higher order modulations and advanced coding techniques. [ABSTRACT FROM PUBLISHER]

This paper investigates various subtleties of applying linear physical-layer network coding (PNC) with $q$ -level pulse amplitude modulation ( $q$ -PAM) in two-way relay channels. A critical issue is how the PNC system performs when the received powers from the two users at the relay are imbalanced. In particular, how would the PNC system perform under slight power imbalance that is inevitable in practice, even when power control is applied? To answer these questions, this paper presents a comprehensive analysis of $q$ -PAM PNC. Our contributions are as follows. First, we give a systematic way to obtain the analytical relationship between the minimum distance of the signal constellation induced by the superimposed signals of the two users (a key performance determining factor) and the channel-gain ratio of the two users, for all $q$ . In particular, we show how the minimum distance changes in a piecewise linear fashion as the channel-gain ratio varies. Second, we show that the performance of $q$ -PAM PNC is highly sensitive to imbalanced received powers from the two users at the relay, even when the power imbalance is slight (e.g., the residual power imbalance in a power-controlled system). This sensitivity problem is exacerbated as $q$ increases, calling into question the robustness of high-order modulated PNC. Third, we propose an asynchronized PNC system in which the symbol arrival times of the two users at the relay are deliberately made to be asynchronous. We show that such asynchronized PNC, when operated with a belief propagation decoder, can remove the sensitivity problem, allowing a robust high-order modulated PNC system to be built. [ABSTRACT FROM AUTHOR]

Many important network design problems are fundamentally combinatorial optimization problems. A large number of such problems, however, cannot readily be tackled by distributed algorithms. The Markov approximation framework studied in this paper is a general technique for synthesizing distributed algorithms. We show that when using the log–sum–exp function to approximate the optimal value of any combinatorial problem, we end up with a solution that can be interpreted as the stationary probability distribution of a class of time-reversible Markov chains. Selected Markov chains among this class yield distributed algorithms that solve the log–sum–exp approximated combinatorial network optimization problem. By examining three applications, we illustrate that the Markov approximation technique not only provides fresh perspectives to existing distributed solutions, but also provides clues leading to the construction of new distributed algorithms in various domains with provable performance. We believe the Markov approximation techniques will find applications in many other network optimization problems. [ABSTRACT FROM AUTHOR]

This paper studies the minimum-age scheduling problem in a wireless sensor network where an access point (AP) monitors the state of an object via a set of sensors. The freshness of the sensed state, measured by the age-of-information (AoI), varies at different sensors and is not directly observable to the AP. The AP has to decide which sensor to query/sample in order to get the most updated state information of the object (i.e., the state information with the minimum AoI). In this paper, we formulate the minimum-age scheduling problem as a multi-armed bandit problem with partially observable arms and explore the greedy policy to minimize the expected AoI sampled over an infinite horizon. To analyze the performance of the greedy policy, we 1) put forth a relaxed greedy policy that decouples the sampling processes of the arms, 2) formulate the sampling process of each arm as a partially observable Markov decision process (POMDP), and 3) derive the average sampled AoI under the relaxed greedy policy as a sum of the average AoI sampled from individual arms. Numerical and simulation results validate that the relaxed greedy policy is an excellent approximation to the greedy policy in terms of the expected AoI sampled over an infinite horizon. [ABSTRACT FROM AUTHOR]

This paper studies the transceiver design of the Gaussian two-pair two-way relay channel (TWRC), where two pairs of users exchange information through a common relay in a pairwise manner. Our main contribution is to show that the capacity of the Gaussian two-pair TWRC is achievable to within $\frac{1}{ 2}$ bit for arbitrary channel conditions. For the outer bound, we derive a genie-aided bound of the Gaussian two-pair TWRC, which is tighter than the cut-set bound. For the inner bound, we develop a hybrid coding scheme involving Gaussian random coding, nested lattice coding, superposition coding, and network-coded decoding. We further present a message-reassembling strategy to decouple the coding design for the user-to-relay and relay-to-user links, so as to provide flexibility to fully exploit the channel randomness. We show that judicious power allocation at the users and at the relay is necessary to approach the channel capacity under various channel conditions. [ABSTRACT FROM AUTHOR]

In this paper, we propose a generalized channel decoding scheme for nonbinary physical-layer network coding (CD-NC) in two-way relay channels (TWRCs), where two source nodes A and B exchange their nonbinary symbols via a relay. The two sources use the same nonbinary low-density parity-check (LDPC) channel code over the integer ring $\mathbb {Z}_M$ and $M$ -pulse-amplitude modulation, respectively. The existing channel decoding schemes for nonbinary network coding suffer severe rate loss compared with the cut-set bound of TWRC, especially in the low-to-medium signal-to-noise ratio regime. The proposed CD-NC can decrease the rate loss. Our contributions are as follows: 1) We develop a generalized nonbinary sum product algorithm (G-SPA) for CD-NC according to the principle of virtual encoding of the superimposed symbols. Simulation results show that our CD-NC can achieve significant performance gains over the conventional nonbinary network coding for both additive white Gaussian noise and fading channels; and 2) We exploit two-dimensional fast-Fourier-transform-based belief propagation (2-D-FFT-BP) and extended min-sum (EMS) decoding algorithms to reduce the decoding complexity of G-SPA. Simulation results show that the 2-D-FFT-BP has the same performance as G-SPA, while EMS can greatly reduce the decoding complexity of G-SPA at the cost of slight performance degradation. [ABSTRACT FROM AUTHOR]

This paper studies the beamforming design for the multiple-input multiple-output (MIMO) multiway relay channel with clustered full data exchange. We formulate the linear signal alignment in the model under a rank-constrained rank-minimization (RCRM) framework. Our contribution is twofold. We decompose the RCRM problem into independent rank-minimization subproblems and put forth an iterative algorithm for the beamforming design. For symmetric antenna setups, our approach advances the state of the art by expanding the achievable degree of freedom (DoF) region, and for asymmetric antenna setups, our approach can be directly applied while prior approaches are not readily applicable. [ABSTRACT FROM AUTHOR]

This paper presents the first network-coded multiple access (NCMA) system prototype operated on high-order modulations up to 16-QAM. NCMA jointly exploits physical-layer network coding (PNC) and multiuser decoding (MUD) to boost throughput of multipacket reception systems. Direct generalization of the existing NCMA decoding algorithm, originally designed for BPSK, to high-order modulations, will lead to huge performance degradation. The throughput degradation is caused by the relative phase offset between received signals from different nodes. To circumvent the phase offset problem, this paper investigates an NCMA system with multiple receive antennas at the access point, referred to as MIMO-NCMA. We put forth a low-complexity symbol-level NCMA decoder that, together with MIMO, can substantially alleviate the performance degradation induced by relative phase offset. To demonstrate the feasibility and advantage of MIMO-NCMA for high-order modulations, we implemented our designs on software-defined radio. Our experimental results show that the throughput of QPSK MIMO-NCMA is double that of both BPSK NCMA and QPSK MUD at SNR = 10 dB. For higher signal-to-noise ratios at which 16-QAM can be supported, the throughput of MIMO-NCMA can be as high as 3.5 times that of BPSK NCMA. Overall, this paper provides an implementable framework for high-order modulated NCMA. [ABSTRACT FROM PUBLISHER]

This paper studies and analyzes a multi-pair MIMO two-way relay (TWR) system from a principal-angle perspective. In this system, users are grouped into pairs and two users in each pair exchange information through a common relay. The transmission scheme consists of two phases. In the uplink phase, the relay’s receive signal space is divided into two subspaces for each pair: in one subspace, the signals of the two users are near-parallel, and physical-layer network coding (PNC) decoding is applied to retrieve network-coded messages; in the other subspace, the two user signals are near-orthogonal, and complete decoding (CD) is applied to retrieve individual user messages. In the downlink phase, the relay’s transmit signal space is split into orthogonal subspaces for each pair, and in each subspace a common message is broadcasted to the two users. Our main contribution is to establish a critical link between the transmission scheme and the concept of principal angle in linear algebra. In particular, principal angle quantizes the degree of orthogonality between the user signals and helps determining how to partition the relay’s receive signal space into PNC decoding subspace and CD decoding subspace. Building on that, we discuss the optimal design of user/relay precoders for both uplink and downlink phases to maximize the asymptotic sum-rate of the proposed scheme at high signal-to-noise ratio (SNR). The analysis and numerical results indicate that our scheme performs close to the cut-set outer bound and significantly outperforms the existing schemes in the literature. [ABSTRACT FROM AUTHOR]

We present an optimal decoder for physical-layer network coding (PNC) in multipath fading channels. Previous studies on PNC have largely focused on the single-path case. For PNC, multipath introduces not only intersymbol interference (ISI) but cross-symbol interference (Cross-SI) between signals simultaneously transmitted by multiple users as well. To overcome these problems, the decoder at the relay of our PNC design makes use of a belief propagation (BP) algorithm to decode the multipath-distorted signals received from multiple users into a network-coded packet. We refer to our multipath decoding algorithm as MP-PNC. Our simulation results show that, benchmarked against synchronous PNC over a one-path channel, the bit-error-rate (BER) performance penalty of MP-PNC under a two-tap International Telecommunication Union (ITU) channel model can be kept within 0.5 dB. Moreover, it outperforms a multiuser detection (MUD)– xor algorithm by 3 dB (MUD– xor decodes the individual information from both users explicitly before performing the xor network-coding mapping). Although the framework of fading-channel PNC presented in this paper is demonstrated based on two- and three-path channel models, our algorithm can be extended to cases with more than three paths. [ABSTRACT FROM PUBLISHER]

This paper addresses joint transceiver and relay design for a wireless multiple-input multiple-output (MIMO) switching scheme that enables data exchange among multiple users. Here, a multiantenna relay linearly precodes the received (uplink) signals from multiple users and forwards the signal in the downlink, where the purpose of precoding is to let each user receive its desired signal with interference from other users suppressed. The problem of optimizing the precoder based on various design criteria is typically nonconvex and difficult to solve. The main contribution of this paper is a unified approach to solve the weighted sum mean square error (MSE) minimization and weighted sum rate maximization problems in MIMO switching. Specifically, an iterative algorithm is proposed for jointly optimizing the relay's precoder and the users' receive filters to minimize the weighted sum MSE. It is also shown that the weighted sum rate maximization problem can be reformulated as an iterated weighted sum MSE minimization problem and can, therefore, be solved similarly to the case of weighted sum MSE minimization. With properly chosen initial values, the proposed iterative algorithms are asymptotically optimal in both high- and low-signal-to-noise-ratio regimes for MIMO switching, either with or without self-interference cancellation (a.k.a., physical-layer network coding). Numerical results show that the optimized MIMO switching scheme based on the proposed algorithms significantly outperforms existing approaches in the literature. [ABSTRACT FROM AUTHOR]

Channel conditions in wireless local area networks (WLANs) are variable due to mobility and interference. Autorate algorithms are commonly used in WLANs to maximize the data rate over the variable physical channel. However, the widely used automatic rate fallback (ARF) algorithm does not work properly in the presence of multiaccess collisions due to its inability to differentiate frame losses caused by link errors from those caused by collisions. This paper proposes an improved ARF algorithm that is capable of differentiating between these two types of losses with minimal modifications to the existing medium access control protocol. The performance evaluations show substantial through-put improvements over ARF and other existing algorithms. [ABSTRACT FROM AUTHOR]