In several wireless settings, channel statistics may be controllable and/or predictable. For instance, next generation reconfigurable antennas have the potential to control channel statistics. Further, the known trajectory and operation protocol of communication satellites results in networks with predictable statistics. These settings give rise to a non-stationary model for which the fundamentals are largely unknown. We consider the canonical two-user broadcast packet erasure channel in which channel statistics vary at a priori known points in time. We consider a multi-modal setting with two non-transient modes (whose lengths scale linearly with the blocklength) and an arbitrary number of transient modes. We provide a new set of outer-bounds on the capacity region of this problem when the encoder has access to causal feedback. The results reveal the significant role of the non-transient mode with higher erasure probability both on the outer and the inner bounds. We show the outer-bounds are achievable in non-trivial regimes, characterizing the capacity region for a wide range of parameters. We also discuss the regimes where the inner and outer bounds diverge and analyze the gap between the two. A key finding of this work is the significant gain of inter-modal coding over the separate treating of individual modes.

To guarantee that every device in industrial Internet of Things (IoT) is reliable for fast data exchange, ultrareliable and low-latency communication (URLLC) technology from 5G is crucial. To reduce latency, typically, only up to 1000 code blocklength is allowed. Indeed, a block error rate (BLER) of less than$10^{-5}$and latency of less than 1 ms are achievable in 5G URLLC. The short code blocklength feature is also required in satellite IoT. Though low-density parity-check (LDPC) decoding via belief propagation (BP) shows promise for achieving low BLER with long blocklength, its BLER is high in short LDPC codes due to error-prone patterns, with the trapping set (TS) being one of the most significant patterns. To alleviate the damage of TS, which can be identified offline, we propose two decoding algorithms named dynamic TS-assisted reinforced BP (DTS-RBP) and TS-assisted relaxation for neural-network BP (TSR-NNBP), respectively. Compared with previous works, only proposed TS assisted decoders can meet URLLC requirements under 308 code blocklength at a 3 dB signal-to-noise ratio (SNR). Moreover, under 128 code blocklength for satellite IoT, our DTS-RBP decoder provides the best memory-performance tradeoff with approximately the same number of iterations as BP.

Streaming codestake a string of source symbols as input and output a string of coded symbols in real time, which eliminate the queueing delay of traditionalblock codesand are thus especially appealing for delay sensitive applications. This work studies the asymptotics of random linear streaming codes (RLSCs) in the large finite-field-size regime under the i.i.d. symbol erasure channel models. Two important scenarios are analyzed: (i) tradeoff between decoding deadline Δ and probability of errorpeassuming infinite memory α = ∞; and (ii) tradeoff between α andpeassuming infinite Δ = ∞. For each scenario, this work derives the corresponding asymptotic constant ρ, power β and decay rate η that satisfype(x) ∼ ρxβe−ηx. The results of (i) and (ii) are then used to study an important code design problem: Under a given target deadline Δ, what is the memory length α needed for the error probabilitypeto be within a factor ofc> 1 of the best possiblep∗eover α. Further analysis also suggests that regardless thecvalue being considered, the necessary memory length is approximately 3–7% of the target deadline Δ when Δ is large, the actual percentage depending on the channel model and the coding rate. Such a prediction is consistent with existing brute-force-based evaluations.

We study the capacity region of the canonical two-user broadcast packet erasure channel when the erasure probabilities vary over the course of the communication block. In particular, we assume the network statistics may be in two distinct modes with a a priori known transition time between the two. We further consider the scenario in which the transmitter is informed of the delivery status of the previously transmitted packets through the feedback channel. We first derive a new set of the outer-bounds for this problem where the slope of the boundaries of the outer-bound region is dominated by the mode with the larger of the two erasure probabilities, and the corner points come from the average probability of each link being active. We show that under certain ratios of the lengths of the modes, these outer-bounds are achievable and thus the capacity region is known. We also discuss the behavior of the inner and outer bounds in other regimes and analyze the gap between the two. One key observation is that coding across the modes is superior to treating each mode as an individual problem.

Future wireless access networks aim to simultaneously support a large number of devices with heterogeneous service requirements, including data rates, error rates, and latencies. While achievable rate and capacity results exist for Gaussian broadcast channels in the asymptotic blocklength regime, the characterization of second-order achievable rate regions for heterogeneous blocklength constraints is not available. Therefore, we investigate a two-user Gaussian broadcast channel (GBC) with heterogeneous blocklength constraints, specified according to users’ channel output signal-to-noise ratios (SNRs). We assume that the user with higher output SNR has a shorter blocklength constraint. We show that with sufficiently large output SNR, the stronger user can perform the early decoding (ED) technique to decode and subtract the interference via successive interference cancellation (SIC). To achieve this goal, we derive an explicit lower bound on the necessary number of received symbols for a successful ED, using an independent and identically distributed Gaussian input. The second-order rate region is also derived. Numerical results show that ED can outperform the hybrid non-orthogonal multiple access scheme when the stronger channel is sufficiently better than the weaker one. Under the considered setting, about 7-dB SNR gain can be achieved compared to treating interference as noise. These results show that ED with SIC is a promising technique for future wireless networks.

This paper investigates the sum rate maximization problem of finite blocklength code (FBC) rate in an interference channel (IC) with strict blocklength constraints. Sum rate maximization using classical first-order approximation can be globally solved by the mixed monotonic programming, which explores its hidden monotonicity. However, under blocklength constraints, more accurate second-order rate approximation is required. To do this, we adopt a shell codebook with latency reducing treating-interference-as-noise decoder, which has higher second- order FBC rates than that using conventional Gaussian codebook. However, our second-order normal-approximation FBC rate suffers from a backoff term called shell dispersion, which not only complicates the rate formula but also makes desired mixed monotonicity difficult to prove. In a general K-user IC, we modify the original shell dispersion term to enable the desired mixed monotonicity to have a slightly lower FBC rate. Two mixed- monotonic functions provided for proposed second-order FBC rates, correspond to two different hidden monotonicities in the rate formulas respectively. Finally, in two-user case K = 2, we can prove the desired mixed monotonicity for FBC sum rate which uses the original shell dispersion term. Simulation results verify that our second-order FBC sum rate maximization can be globally solved and provide a 59 percent rate prediction improvement over the first-order one, with nearly same iterations.

Delayed channel state information (CSI) feedback was shown to be very helpful in enlarging the capacity region of the two-user broadcast packet erasure channel (PEC), even with single-user feedback. However, feedback link itself requires additional resources and may also cause additional delay to data transmission. In this work, we aim to study how to optimally tradeoff the number of feedback bits and the reliable forward communication rate. In our model, one receiver does not provide its CSI while the other one can alternate between delayed CSI feedback and no feedback. This model includes the intermittent single-user feedback as a special case. Our achievability is an extension of previous opportunistic network coding such that the network coding gain can still be enjoyed even when the single-user feedback is not always available. Interestingly, when two users have the same link erasure probabilities, boundaries of the capacity regions are identified since they can be achieved by the proposed schemes. Our results also reveal that even when the single-user feedback is alternating, strictly positive capacity benefits can be attained over the no-feedback capacity.

The generative adversarial network (GAN) aims to approximate an unknown distribution via a parameterized neural network (NN). While GANs have been widely applied in reinforcement and semi-supervised learning as well as computer vision tasks, selecting their parameters often needs an exhaustive search and only a few selection methods can be proved to be theoretically optimal. One of the most promising GAN variants is the Wasserstein GAN (WGAN). Prior work on optimal parameters for WGAN is limited to the linear-quadratic-Gaussian (LQG) setting, where the NN is linear and the data is Gaussian. In this paper, we focus on the characterization of optimal WGAN parameters beyond the LQG setting. We derive closed-form optimal parameters for one-dimensional WGANs with non-linear sigmoid and ReLU activation functions. Extensions to high-dimensional WGANs are also discussed. Empirical studies show that our closed-form WGAN parameters have good convergence behavior with data under both Gaussian and Laplace distributions.

Streaming codes eliminate the queueing delay and are an appealing candidate for low latency communications. This work studies the tradeoff between error probability peand decoding deadline ∆ of infinite-memory random linear streaming codes (RLSCs) over i.i.d. symbol erasure channels (SECs). The contributions include (i) Proving pe(∆) ∼ ρ∆−1.5e−η∆. The asymptotic power term ∆−1.5of RLSCs is a strict improvement over the ∆−0.5term of random linear block codes; (ii) Deriving a pair of upper and lower bounds on the asymptotic constant ρ, which are tight (i.e., identical) for one specific class of SECs; (iii) For any c > 1 and any decoding deadline ∆, the c-optimal memory length $\alpha _c^{\ast}(\Delta )$ is defined as the minimal memory length α needed for the resulting peto be within a factor of c of the best possible $p_e^{\ast}$ under any α, an important piece of information for practical implementation. This work studies and derives new properties of $\alpha _c^{\ast}(\Delta )$ based on the newly developed asymptotics.

Byzantine distributed quickest change detection (BDQCD) is a crucial problem in cyber-physical security. The challenge of this problem is that an AI plus IoT (AIoT) network needs to detect the change as quickly as possible, subject to a false alarm rate, to prevent device damage. In the BDQCD problem, dealing with compromised meters also becomes a challenge since these meters can collaboratively form an attack to lengthen the detection delay in an IoT network. Here we consider the network where a fusion center monitors the occurrence of an abrupt event through a bunch of distributed meters that may be compromised. To solve the challenge, a new coded framework for BDQCD utilizing bounded distance decoding at the fusion center is proposed. First, under sufficient meter-to-fusion-center link capacity, we achieve a theoretical result that the detection delay of our scheme can be asymptotically optimal in special cases. Next, new codebooks under insufficient link capacities are designed based on the theoretical result. Through the simulation results, our coded BDQCDs outperform the state-of-the-art works by achieving significantly shorter detection delay under various attacks.

Future wireless access networks will simultaneously support a large number of devices with heterogeneous service requirements. These include data rates, error rates, and latencies. While capacity results exist for Gaussian broadcast channels in the asymptotic regime, the characterization of second-order achievable rate region for different blocklength constraints is not available. Therefore, we investigate a two-user Gaussian broadcast channel (GBC) with heterogeneous blocklength constraints, specified according to users’ channel output signal to noise ratios (SNRs) under a maximal input power constraint and an average error probability constraint. We show that with sufficiently large output SNR, the stronger user can invoke the technique named early decoding (ED) to decode the interference. Then the successive interference cancellation (SIC) is performed. We derive the rate region of the considered setting with individual and also sum power constraints and compare with the hybrid non-orthogonal multiple access (HNOMA) scheme. Numerical results show that under sum power constraint, ED has a larger rate region than HNOMA at the region where the weaker user’s rate is sufficiently large, when the gain of the better channel is sufficiently larger than the weaker one. The above observation makes ED with SIC a promising technique for future wireless networks.

Channel dispersion quantifies the convergence speed of coding rate to channel capacity under different latency constraints. Under the setting of packet erasure channels (PECs) with Bernoulli packet arrivals, this work characterizes the channel dispersions of random linear streaming codes (RLSCs) and MDS block codes, respectively. New techniques are developed to quantify the channel dispersion of sequential (non-block-based) coding, the first in the literature. The channel dispersion expressions are then used to compare the levels of error protection between RLSCs and MDS block codes. The results show that if and only if the target error probability peis smaller than a threshold (≈0.1774), RLSCs offer strictly stronger error protection than MDS block codes, which is on top of the already significant 50% latency savings of RLSCs that eliminate the queueing delay completely.

Streaming codestake a string of source symbols as input and output a string of coded symbols in real time, which eliminate the queueing delay of traditionalblock codesand are thus especially appealing for delay sensitive applications. Existing works on streaming code performance either focused on the asymptotic error-exponent analyses, or on the optimal code construction underdeterministic adversarial channel models. In contrast, this work analyzes the exact error probability ofrandom linear streaming codes(RLSCs) in the large field size regime over the stochastic i.i.d. symbol erasure channel model. A closed-form expression of the error probability of large-field-size RLSCs is derived under, simultaneously, the finite memory length and decoding deadline constraints. The result is then used to examine the intricate tradeoff between memory length (complexity), decoding deadline (delay), code rate (throughput), and error probability (reliability). Numerical evaluation shows that under the same code rate and error probability requirements, the end-to-end delay of RLSCs is 40–48% of that of the optimal block codes (i.e., MDS codes). This implies that switching from block codes to streaming codes not only eliminates the queueing delay completely (which accounts for the initial 50% of the delay reduction) but also improves the reliability (which accounts for the additional 2–10% delay reduction).

The problem of computing the modulo-sum of independent messages over a finite-field erasure multiple access channel is investigated. The focus is on the role of delayed state feedback for function computation over state dependent multiple access channels. For the two-user case, a set of new outer bounds on the non-feedback computation capacity region are developed, which strictly improve the state of the art by Khistiet al., 2013. As a result, a previously unsettled question is answered in the affirmative: delayed state feedback strictly increases computation capacity for the two-user erasure multiple access channel universally. The proof leverages the subset entropy inequalities by Madiman and Tetali, 2010, Jianget al., 2014, and submodularity of conditional entropies. For the achievability part of the non-feedback case, an achievable computation rate region is derived by generalizing the proposed schemes in Khistiet al., 2013. Beyond the two-user case, the$K$-user case is also investigated, with emphasis on the large system regime, where$K$is the number of users. For the non-feedback case, we propose a grouping scheme which has higher computation rate than that of the conventional “compute-and-forward” (CF) scheme. Furthermore, with a growing number of users, the proposed grouping scheme strictly outperforms the conventional “decode-and-forward (DF)” scheme when the erasure probability is smaller than$1-e^{\frac {1}{e}}\approx 0.3078$. This is in contrast to the two-user case where the currently best known achievability (Khistiet al., 2013) coincides with the better one betweenDFandCF. For the case with delayed state feedback, a new hybrid-ARQ-type scheme is proposed, and in the large system regime, it achieves a computation rate scaling like$\Omega \left({\frac {1}{\log (K)}}\right)$, much higher than the scaling$\Theta \left({\frac {1}{K}}\right)$achieved by the grouping scheme without feedback.

In this work, we investigate a two-user Gaussian broadcast channel (GBC) with heterogeneous blocklength constraints, specified according to users' channel output signal to noise ratios (SNRs). Unlike traditional GBC where two users have the same blocklength constraints, here the user with higher output SNR may have a shorter blocklength constraint. Then it is unclear whether this user can decode the interference to perform successive interference cancellation (SIC) or not. We argue that with sufficient large output SNR, this user can invoke the technique named as the early decoding to decode the interference. Then SIC can proceed. We derive an explicit lower bound on the necessary blocklength for successful early decoding, using an independent and identically distributed Gaussian input, given a maximal input power constraint and an average error probability constraint. A huge SNR gain can be achieved over treating interference as noise when SIC is applied with the aid of early decoding.

Motivated by the applications for low-delay communication networks, the finite-length analysis, or channel dispersion identification, of the multi-user channel is very important. Recent studies also incorporate the effects of feedback in point-to-point and common-message broadcast channels (BCs). However, with private messages and feedback, finite-length results for BCs are much more scarce. Though it is known that feedback can strictly enlarge the capacity, the ultimate feedback capacity regions remain unknown for even some classical channels including Gaussian BCs. In this work, we study the two-user broadcast packet erasure channel (PEC) with causal feedback, which is one of the cleanest feedback capacity results and the capacity region can be achieved by elegant linear network coding (LNC). We first derive a new finite-length outer bound for any LNCs and then accompanying inner bound by analyzing a three-phase LNC. For the outer-bound, we adopt a linear-space-based framework, which can successfully find the LNC capacity. However, naively applying this method in finite-length regime will result in a loose outer bound. Thus a new bounding technique based on carefully labelling each time slot according to the type of LNC transmitted is proposed. Simulation results show that the sum-rate gap between our inner and outer bounds is within 0.02 bits/channel use. Asymptotic analysis also shows that our bounds bracket the channel dispersion of LNC feedback capacity for broadcast PEC to within a factor of Q-l (E/2)/Q-l (E).

Streaming codes take a string of source symbols as input and output a string of coded symbols in real time, which effectively eliminate the queueing delay and are regarded as a promising scheme for low latency communications. Aiming at quantifying the fundamental latency performance of random linear streaming codes (RLSCs) over i.i.d. symbol erasure channels, this work derives the exact error probability under, simultaneously, the finite memory length and finite decoding deadline constraints. The result is then used to examine the tradeoff among memory length (complexity), decoding deadline (delay), and error probability (reliability) of RLSCs for the first time in the literature. Two critical observations are made: (i) Too much memory can adversely impact the performance under a finite decoding deadline constraint, a surprising finding not captured by the traditional wisdom that large memory length monotonically improves the performance in the asymptotic regime; (ii) The end-to-end delay of the RLSC is roughly 50% of that of the MDS block code when under identical code rate and error probability requirements. This implies that switching from block codes to RLSCs not only eliminates the queueing delay (thus 50%) but also has little negative impact on the error probability.

With the recent emergence of many low-latency applications over wireless networks, the need for accurate finite-length analysis of channel coding over multi-user wireless channels is ever increasing. This paper focuses exclusively on the two-user broadcast packet erasure channel (PEC) with causal feedback, for which existing results show that various linear network coding (LNC) schemes can attain the broadcast capacity region when the block length approaches infinity. Instead of the asymptotic capacity-based analysis, this work derives the exact value of the LNC-based broadcast channel dispersion. Our approach is based on a new explicit characterization of the optimal LNC scheme under any arbitrarily given finite block length. The results show that among all existing asymptotically capacity-achieving LNC schemes, one (class) of them is provably finite-length optimal. By analyzing its second-order asymptotic, we have thus derived the exact (optimal) LNC broadcast channel dispersion, which closes the gap of the state-of-the-art inner and outer bounds previously derived in Lin et al. ISIT 2021

Achievable data rates in wireless systems rely heavily on the available channel state information (CSI) throughout the network. However, feedback links, which provide this information, are scarce, unreliable, and subject to security threats. In this work, we study the impact of having intermittent feedback links on the capacity region of the canonical two-user erasure broadcast channels. In our model, at any time instant, each receiver broadcasts its CSI, and at any other node, this information either becomes available with unit delay or gets erased. For this setting, we develop a new set of outer bounds to capture the intermittent nature of the feedback links. These outer bounds depend on the probability that the CSI from both receivers are erased at the transmitter. In particular, if at any time, the CSI from at least one of the two receivers is available at the other two nodes, then the outer-bounds match the capacity with global delayed CSI. We also provide capacity-achieving transmission strategies under certain scenarios, and we establish a connection between this problem and Blind Index Coding with feedback.

The Byzantine distributed quickest change detection (BDQCD) is studied, where a fusion center monitors the occurrence of an abrupt event through a bunch of distributed sensors that may be compromised. We first consider the binary hypothesis case where there is only one post-change hypothesis and prove a novel converse to the first-order asymptotic detection delay in the large mean time to a false alarm regime. This converse is tight in that it coincides with the currently best achievability shown by Fellouris et al.; hence, the optimal asymptotic performance of binary BDQCD is characterized. An important implication of this result is that, even with compromised sensors, a 1-bit link between each sensor and the fusion center suffices to achieve asymptotic optimality. To accommodate multiple post-change hypotheses, we then formulate the multi-hypothesis BDQCD problem and again investigate the optimal first-order performance under different bandwidth constraints. A converse is first obtained by extending our converse from binary to multi-hypothesis BDQCD. Two families of stopping rules, namely the simultaneous d-th alarm and the multi-shot d-th alarm, are then proposed. Under sufficient link bandwidth, the simultaneous d-th alarm, with d being set to the number of honest sensors, can achieve the asymptotic performance that coincides with the derived converse bound; hence, the asymptotically optimal performance of multi-hypothesis BDQCD is again characterized. Moreover, although being shown to be asymptotically optimal only for some special cases, the multi-shot d-th alarm is much more bandwidth-efficient and energy-efficient than the simultaneous d-th alarm. Built upon the above success in characterizing the asymptotic optimality of the BDQCD, a corresponding leader-follower Stackelberg game is formulated and its solution is found.

We characterize the capacity region of the two-user broadcast packet erasure channel (PEC) with single-user delayed channel state information (CSI). More precisely, we assume one receiver does not provide its channel state to the other two nodes (the other receiver and the transmitter), while the other receiver reveals its state globally with unit delay. This is a hybrid CSI at the transmitter (CSIT) setting where the transmitter has the delayed CSI of one user but not the other. Previous results developed opportunistic network coding schemes for this setting, which strictly enlarge the achievable rate region compared to the no-CSIT baseline. Characterization of the capacity region with single-user delayed CSI, however, remained open. In this work, we develop an improved achievability strategy and show that the capacity region, surprisingly, matches that of the broadcast PEC with global delayed CSI of both users. The key to such improvement over previous results is a new precoding strategy for the retransmission phase of the opportunistic network coding scheme. It harnesses the single-user delayed CSI in the retransmission phase, so that interference from the feedback receiver can be aligned at the other receiver. Besides the broadcast PEC with two private messages, an extension to a model with an additional common message is also provided and the corresponding capacity region with single-user CSI also matches that with global delayed CSI. Finally, further extensions to three-user cases are also provided.

5G downlink communications are expected to suffer more from the intermittent link connectivity, and studying the erasure broadcast channel (BC) provides the fundamental understanding of their performance. Recently, the capacity region of two-user erasure BC with single-user delayed channel state information (CSI) was characterized, where one receiver does not provide its channel state to the transmitter and the other receiver, while the other receiver feeds back its state globally with unit delay. Surprisingly, the capacity region with single-user delayed CSI matches that of the erasure BC with global delayed CSI of both users. When two links have same erasure probabilities, this result is valid even when a common message intended for both users is required besides two private messages. The capacity in this case is easily achieved by adding a phase multicasting the common message after the transmission of private messages. However, when erasure probabilities are unequal, this scheme is clearly not capacity-achieving since the rate of the last phase will be limited by the weaker user having larger erasure probability. We propose a scheme which transmits the common message with rate higher than the link capacity of the weaker user in the last phase but still can ensure the decodability. The key is to simultaneously create equations of the common message at the weaker receiver and re-transmit private bits before the last phase. The proposed scheme achieves the converse under unequal link erasure probabilities, and the capacity with common and private messages is fully characterized under single-user delayed CSI.

Streaming codes encode a string of source packets and output a string of coded packets in real time, which eliminate the queueing delay of block coding and are thus especially suitable for delay-sensitive applications. This work studies random linear streaming codes (RLSCs) and i.i.d. packet erasure channels. While existing works focused on the asymptotic error-exponent analyses, this work characterizes the error rate in the finite memory length regime and the contributions include: (i) A new information-debt-based description of the error event; (ii) A matrix-based characterization of the error rate; (iii) A closed-form approximation of the error rate that is provably tight for large memory lengths; and (iv) A new Markov-chainbased analysis framework, which can be of independent research interest. Numerical results show that the approximation, i.e. (iii), closely matches the exact error rate even for small memory length (≈ 20). The results can be viewed as a sequential- coding counterpart of the finite length analysis of block coding [Polyanskiy et al. 10] under the specialized setting of RLSCs.

This paper investigates the transmission energy minimization problem for the two-user downlink with strictly heterogeneous latency constraints. To cope with the latency constraints and to explicitly specify the trade-off between blocklength (latency) and reliability the normal approximation of the capacity of finite blocklength codes (FBCs) is adopted, in contrast to the classical Shannon capacity formula. We first consider the non-orthogonal multiple access (NOMA) based transmission scheme. However, due to heterogeneous latency constraints and channel conditions at receivers, the conventional successive interference cancellation may be infeasible. We thus study the problem by considering heterogeneous receiver conditions under different interference mitigation schemes and solve the corresponding NOMA design problems. It is shown that, though the energy function is not convex and does not have closed form expression, the studied NOMA problems can be globally solved semi-analytically and with low complexity. Moreover, we propose a hybrid transmission scheme that combines the time division multiple access (TDMA) and NOMA. Specifically, the hybrid scheme can judiciously perform bit and time allocation and take TDMA and NOMA as two special instances. To handle the more challenging hybrid design problem, we propose a concave approximation of the FBC rate/capacity formula, by which we obtain computationally efficient and high-quality solutions. Simulation results show that the hybrid scheme can achieve considerable transmission energy saving compared with both pure NOMA and TDMA schemes.

Sequential change point detection with multiple decentralized sensors is studied. Each sensor makes a local decision based on its own observations and reports it through a bandlimited link to a fusion center, which then decides whether the change has occurred. Since sensors in many applications such as cyber-physical systems are prone to a number of attacks such as Byzantine attacks, combating such a security breach becomes one of the most crucial issues. Previous works on sequential change detection under Byzantine attacks only focus on binary-hypothesis case, which significantly limits the applicability. In this paper, we consider the extension to the multi-hypothesis setting. We show that naively extending the existing method from the binary case to the multi-hypothesis one can result in a catastrophic event preventing the fusion center from making a conclusive decision. Thus we propose the other two new methods by allowing each sensor to cast multiple local alarms, and both can avoid this catastrophic event and improve the asymptotic detection delay. In analyzing detection delays of our multi-hypothesis schemes, we also show that for each hypothesis, asymptotically, it suffices to focus on the competing hypothesis that is closest in Kullback-Leibler distance. Through large sensor analysis, we also show that as the number of honest sensors grows, one of the proposed scheme, called the simultaneous rule, approaches the optimal performance within a factor of 2.

The Byzantine distributed sequential change detection (BDSCD) problem is studied, where a fusion center monitors an abrupt event occurring at an unknown time through a bunch of distributed sensors. It is assume that a part of the sensors are compromised and each sensor, honest or compromised, communicates with the fusion center via a noiseless link. A new converse for this problem is presented whose first-order asymptotic delay subject to a certain false alarm rate coincides with the currently best known result achieved by the consensus rule proposed by Fellouris et al. This result characterizes the first-order asymptotic performance of BDSCD and shows that 1-bit links suffice to achieve the asymptotic optimality. The proof of the converse involves constructing an attack strategy, called the reverse attack, introducing a genie that gives the fusion center the identities of a subset of honest sensors and observations at each sensor used for generating its local report, and transforming the problem into an equivalent non-Byzantine sequential change detection but with reduced number of honest sensors.

We characterize the capacity region of the two-user erasure broadcast channel (BC) with single-user delayed channel state information (CSI). More precisely, we assume one receiver does not provide its channel state to the other two nodes (the other receiver and the transmitter), while the other receiver reveals its state globally with unit delay. This is a "DN" hybrid CSI at the transmitter (CSIT) setting where the transmitter has the delayed CSI of one user but not the other. Previous results developed opportunistic network coding schemes for this DN setting, which strictly enlarge the achievable rate region compared to the no-CSIT baseline. Characterization of the capacity region for the DN setting, however, remained open. In this work, we develop an improved achievability strategy and show that the capacity region, surprisingly, matches that of the erasure BC with global delayed CSI of both users. The key to such improvement over previous results is a new precoding strategy for the retransmission phase of the opportunistic network coding scheme. It harnesses the single-user delayed CSI in the retransmission phase, so that interference from the "D" receiver can be aligned at the "N" receiver. Besides erasure BCs with two private messages, an extension to BCs with an additional common message is also provided.

Recently, we showed that, rather surprisingly, the capacity region of the two-user erasure broadcast channel with global delayed channel state information (CSI) can be achieved with single-user delayed CSI only. More precisely, we assumed one receiver does not provide its channel state to the other two nodes (the other receiver and the transmitter), while the other receiver reveals its state globally with unit delay. In this work, we consider a more general setting in which feedback links are intermittent. To be precise, at any time instant, each receiver broadcasts its CSI, and this information either becomes available to the other two nodes or gets erased. For this setting, we develop a new set of outer bounds to capture the intermittent nature of the feedback links. These outer bounds depend on the probability that both feedback links are erased rather than the individual erasure probability of each feedback link. This result matches our earlier findings for the single-user delayed CSI scenario. We also provide a capacity-achieving recursive communication protocol for the scenario in which feedback links are fully correlated.

Cyber-physical systems, such as smart grids, have received lots of attention recently. Unfortunately, security breaches in cyber-physical systems can result in catastrophic consequences, thus needing to be carefully monitored. For example, abnormal voltage quality events, which are more likely to happen because of unstable renewable energy sources in smart grids, harm delicate electronic devices. We thus focus on the quickest classification, or multi-hypothesis quickest change detection, which jointly detects and classifies multiple abnormal events. Both the classification delay and misclassification probability need to be low. Multiple smart meters are adopted, where each meter transmits its local decision to a fusion center for making the final decision. For energy saving, the bandwidth (link capacity) between each meter and the fusion center is limited to be one bit. Moreover, some meters may be faulty and mislead the final decision. To combat these faulty meters under the limited bandwidth, a code-based framework for quickest classification is proposed. Our contribution is two-fold. First, a new local decision rule based on the stochastic ordering theory is proposed. Compared with existing matrix-cumulative-sums algorithm, the newly proposed local decision rule has lower complexity and comparable performance. Second, a new fusion method based on codebook switching and minimum Hamming distance rule is developed. Compared with existing fault-tolerant methods, the newly-developed method can significantly lower the misclassification probabilities.

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.

The goal of the smart grid is to develop a more reliable, secure, and environmentally friendly power grid. Unfortunately, power quality (PQ) events are more likely to happen due to unstable renewable energy sources in smart grids. We thus focus on the quickest classification, or multihypothesis quickest change detection, which jointly detects and classifies multiple abnormal PQ events. Both the classification delay and misclassification probability are aimed to be minimized. Multiple smart meters in the grid are used, where each meter transmits its local decision to a fusion center for making final decisions. For energy saving, the capacity between each meter and the fusion center is limited to be one bit. Moreover, some meters may be faulty and misleading the final decision. To combat these faulty meters under limited link capacity, a code- based framework for quickest classification is proposed. Our contribution is twofold. First, new local decision rule based on stochastic ordering theory is proposed, which has lower complexity and competing performance compared with existing matrix Cumulative Sums (CUSUM). Second, a new fusion method based on codebook switching and minimum Hamming distance rule is developed, which can significantly lower the misclassification probability.

The problem of computing the modulo-sum of messages over a finite-field erasure multiple access channel (MAC) is studied, and the role of feedback for function computation is explored. Our main contribution is two-fold. First, a new outer bound on the non-feedback computation capacity is proved, which strictly improves the state of the art [1]. The new outer bound answers a previously unsettled question in the affirmative: delayed state feedback strictly increases computation capacity for the two-user erasure MAC universally. The proof leverages the subset entropy inequality by Madiman and Tetali [2]. Second, focusing on the family of linear coding schemes with hybrid-ARQ-type retransmissions, we develop the optimal computation rate with delayed state feedback. For the considered family of schemes, it is always sub-optimal to compute modulo-sum by decoding all messages first. This is in contrast to the nonfeedback case [1] where sometimes the aforementioned “decode-all” strategy can reach the best known achievable rates.

The modulo-sum computation of messages over a K-user finite-field erasure multiple access channel (MAC) is studied, with emphasis on the role of feedback in the large system regime. For the non-feedback case, we propose a grouping scheme which has higher computation rate than that of the conventional “compute-and-forward” (CF) scheme where each transmitter uses the same linear code and the receiver leverages the additive structure of the multiple access channel to compute the modulo sum. Furthermore, with a growing number of users, the proposed grouping scheme strictly outperforms the conventional “decode-and-forward (DF)” scheme when the erasure probability is smaller than 1-e1/e≈ 0.3078, where the receiver first decodes messages of all users and then computes the modulo sum. This is in contrast to the two-user case where the currently best known achievability, reported by Khisti, Hern, and Narayanan in 2013, coincides with the better one between DF and CF. For the case with delayed state feedback, a new hybrid-ARQ-type scheme is proposed, and in the large system regime, it achieves a computation rate scaling like Ω(1/log(K)), much higher than the scaling Θ(1/K) achieved by the grouping scheme without feedback. Our result hints at significant gain in function computation due to feedback in the large system regime when the transmitters are connected intermittently to the receiver, in sharp contrast to the static case where feedback provides no gain at all.

This paper considers the joint design of training and data transmission in physical-layer secret communications, and examines the role of artificial noise (AN) in both of these phases. In particular, AN in the training phase is used to prevent the eavesdropper from obtaining accurate channel state information (CSI), whereas AN in the data transmission phase can be used to mask the transmission of confidential messages. By considering AN-assisted training and secrecy beamforming, we first derive bounds on the achievable secrecy rate and utilize them to obtain approximate secrecy rate expressions that are asymptotically tight at high SNR. By maximizing these expressions, power allocation policies between signal and AN in both training and data transmission phases are then proposed for conventional and AN-assisted training-based schemes, respectively. We show that the optimal AN power at high SNR should be non-vanishing with respect to the total power, and that AN usage can be more effective in the training phase than in the data transmission phase when the coherence time is large. However, at low SNR, we show that AN cannot be effectively utilized due to the lack of accurate CSI, and thus, one can often do better without. Numerical results are presented to verify our theoretical claims.

We consider a cloud radio access network (CRAN) with full duplex (FD) remote radio heads (RRHs) and half duplex mobile users. Compared with half duplex RRHs, though FD-RRHs can simultaneously transmit and receive data streams, they also suffer from new interference sources such as self-interference and inter-RRH interference. With FDRRHs, the downlink mobile users (DMUs) are also interfered by signals from the uplink mobile users (UMUs). To mitigate the interference aforementioned, new beamforming designs are required for downlink transmission and uplink reception at the FD-RRHs. We propose to minimize the sum power of CRAN by optimizing the beamformers of FD-RRHs and power control of UMUs, under quality of service constraints for both DMUs and UMUs. While the considered problem is not convex due to the new interference sources, we can solve it by second-ordercone-program (SOCP) based alternating optimization (AO) with guaranteed convergence to the KKT point. Moreover, we show that there still holds an interesting uplink-downlink duality in our problem. This duality is exploited to develop another AO solver with the same performance. The duality-based AO solver has much lower complexity than the SOCP-based one, and the simulation results show that both AO solvers yields to smaller sum power compared with the half duplex CRAN.

State-dependent broadcast channels (BC) with heterogeneous channel state information available at the transmitter (CSIT) are studied. The heterogeneity of CSIT lies in the timeliness of channel state that governs the link from the transmitter to different receivers - CSI of each link can be perfectly (causally or non-causally), delayed, or not available at the transmitter. We focus on the erasure BC and the bursty Gaussian BC, where the channel states are governed by memoryless Bernoulli processes, independent across users. For the erasure BC with perfect single-user CSIT, we characterize its capacity region regardless of the CSIT of the other user and show that this capacity region strictly contains that with no CSIT. For the case with delayed single-user CSIT, we propose an opportunistic network coding scheme that achieves a strictly larger rate region than the no-CSIT capacity region. These results are extended to the bursty Gaussian BC, where for the perfect single-user CSIT scenario, the capacity region is characterized to within a bounded gap; and for the delayed single-user CSIT scenario, a rate region based the opportunistic network coding scheme is derived. As a corollary, single-user CSIT is able to increase the sum degrees of freedom (DoF) for bursty Gaussian BC. Our result is in sharp contrast to the recent negative result by Davoodi and Jafar [1], where it is shown that for fast-fading MISO broadcast channel, single-user CSIT does not help at all in terms of sum DoF.

This paper considers noisy Wyner-Ziv coding (WZC), in which a remote noisy source is compressed with side information at the decoder only. The decoder side information is not limited to being Gaussian, thus this noisy WZC problem cannot be transformed into the conventional one tailored for noiseless sources. A new coding structure, named the residual-quantization (RQ) based noisy WZC, is proposed to solve the problem. This scheme explicitly constructs the theoretical auxiliary random variable to facilitate optimal reconstruction of the noisy source. In this two-stage encoder, the noisy source is quantized twice and the quantization error (residue) of the first stage is the input of the second stage. By sending only the quantization index of the second stage to the decoder, the corresponding code rate can theoretically approach the noisy WZC bound. Moreover, the RQ-based noisy WZC is implemented using graph-based codes. The main challenge is that it is necessary to design a codebook that is simultaneously good for source and channel coding for the first stage quantization, since this quantization code also acts as a channel code at the decoder. This problem is solved by constructing a low-density parity check (LDPC) code with edge degrees optimized for channel coding, and enhancing its performance for source coding by using a modified reinforced belief-propagation quantization algorithm. Simulation results show that the noisy Wyner-Ziv bounds can be practically approached by our implementation. In addition, the proposed implementation offers more flexibility in the code rates compared with the existing practical designs, making it more suitable for emerging applications such as fronthaul compression.

This paper considers an energy-efficient packet scheduling problem over quasi-static block fading channels. The goal is to minimize the total energy for transmitting a sequence of data packets under the first-in-first-out rule and strict delay constraints. Conventionally, such a design problem is studied under the assumption that the packet transmission rate can be characterized by the classical Shannon capacity formula, which, however, may provide inaccurate energy consumption estimation, especially when the code blocklength is finite. In this paper, we formulate a new energy-efficient packet scheduling problem by adopting a recently developed channel capacity formula for finite blocklength codes. The newly formulated problem is fundamentally more challenging to solve than the traditional one, because the transmission energy function under the new channel capacity formula neither can be expressed in closed form nor possesses desirable monotonicity and convexity in general. We analyze conditions on the code blocklength for which the transmission energy function is monotonic and convex. Based on these properties, we develop efficient offline packet scheduling algorithms as well as a rolling-window-based online algorithm for real-time packet scheduling. Simulation results demonstrate not only the efficacy of the proposed algorithms but also the fact that the traditional design using the Shannon capacity formula can considerably underestimate the transmission energy for reliable communications.

This paper considers an energy-efficient packet scheduling problem over green data networks, aiming at minimizing the transmission energy subject to the First-In-First-Out and strict delay constraints. Traditionally, such a problem is studied based on the classical Shannon capacity formula. However, Shannon capacity is valid only when the code blocklength approaches infinity and therefore is not practical for some applications in 5G system which allow short delays only. In this paper, we formulate the packet scheduling problem using the recently developed channel capacity formula for the finite blocklength code. It turns out that the newly formulated problem is much more challenging to solve than the traditional ones. Nevertheless, we analytically show that our scheduling problem can possess certain desirable monotonic and convex properties. Based on these properties, by applying a successive upper bound minimization (SUM) method, an iterative packet scheduling algorithm is proposed to efficiently solve the considered problem. Simulation results show that, compared with the proposed design using the finite blocklength channel capacity, the traditional design based on Shannon capacity will seriously underestimate the required transmission energy for reliable communications.

When multiple users share the same resource for physical layer cooperation such as relay terminals in their vicinities, this shared resource may not be always available for every user, and it is critical for transmitting terminals to know whether other users have access to that common resource in order to better utilize it. Failing to learn this critical piece of information may cause severe issues in the design of such cooperative systems. In this paper, we address this problem by investigating a two-pair two-way relay channel with an intermittently available relay. In the model, each pair of users need to exchange their messages within their own pair via the shared relay. The shared relay, however, is only intermittently available for the users to access. The accessing activities of different pairs of users are governed by independent Bernoulli random processes. Our main contribution is the characterization of the capacity region to within a bounded gap in a symmetric setting, for both delayed and instantaneous state information at transmitters. An interesting observation is that the bottleneck for information flow is the quality of state information (delayed or instantaneous) available at the relay, not those at the end users. To the best of our knowledge, our work is the first result regarding how the shared intermittent relay should cooperate with multiple pairs of users in such a two-way cooperative network.

We consider the block Rayleigh fading multiple-input multiple-output (MIMO) wiretap channel with no prior channel state information (CSI) available at any of the terminals. The channel gains remain constant within a coherence interval of T symbols, and then change to another independent realization in the next coherence interval. The transmitter, the legitimate receiver, and the eavesdropper have nt, nr, and ne antennas, respectively. We determine the exact secure degrees of freedom (s.d.o.f.) of this system when T ≥ 2min(nt,nr). We show that, in this case, the s.d.o.f. is exactly equal to (min(nt,nr)-ne)+(T -min(nt,nr))/T. The first term in this expression can be interpreted as the eavesdropper with ne antennas taking away ne antennas from both the transmitter and the legitimate receiver. The second term can be interpreted as a fraction of the s.d.o.f. being lost due to the lack of CSI at the legitimate receiver. In particular, the fraction loss, min(nt,nr)/T, can be interpreted as the fraction of channel uses dedicated to training the legitimate receiver for it to learn its own CSI. We prove that this s.d.o.f. can be achieved by employing a constant norm channel input, which can be viewed as a generalization of discrete signalling to multiple dimensions.

We consider the block Rayleigh fading multiple-input multiple-output (MIMO) wiretap channel with no prior channel state information (CSI) available at any of the terminals. The channel gains remain constant in a coherence time of T symbols, and then change to another independent realization. The transmitter, the legitimate receiver and the eavesdropper have nt, nrand neantennas, respectively. We determine the exact secure degrees of freedom (s.d.o.f.) of this system when T ≥ 2 min(nt, nr). We show that, in this case, the s.d.o.f. is exactly (min(nt, nr) − ne)+(T − min(nt, nr))/T. The first term can be interpreted as the eavesdropper with neantennas taking away neantennas from both the transmitter and the legitimate receiver. The second term can be interpreted as a fraction of s.d.o.f. being lost due to the lack of CSI at the legitimate receiver. In particular, the fraction loss, min(nt, nr)/T, can be interpreted as the fraction of channel uses dedicated to training the legitimate receiver for it to learn its own CSI. We prove that this s.d.o.f. can be achieved by employing a constant norm channel input, which can be viewed as a generalization of discrete signalling to multiple dimensions.

This paper considers the multiantenna multiple-access relay channel (MARC), in which multiple users transmit messages to a common destination with the assistance of a relay. In a variety of MARC settings, the dynamic decode-and-forward (DDF) protocol is very useful due to its outstanding rate performance. However, the lack of good structured codebooks so far hinders practical applications of DDF for MARC. In this work, two classes of structured MARC codes are proposed: 1) one-to-one relay-mapper-aided multiuser lattice coding (O-MLC); and 2) modulo-sum relay-mapper-aided multiuser lattice coding (MS-MLC). The former enjoys better rate performance, whereas the latter provides more flexibility to tradeoff between the complexity of the relay mapper and the rate performance. It is shown that, in order to approach the rate performance achievable by an unstructured codebook with maximum-likelihood decoding, it is crucial to use a new K-stage coset decoder for structured O-MLC instead of the one-stage decoder proposed in previous works. However, if O-MLC is decoded with the one-stage decoder only, it can still achieve the optimal DDF diversity-multiplexing gain tradeoff in the high signal-to-noise ratio regime. As for MS-MLC, its rate performance can approach that of the O-MLC by increasing the complexity of the modulo-sum relay-mapper. Finally, for practical implementations of both O-MLC and MS-MLC, practical short-length lattice codes with linear mappers are designed, which facilitate efficient lattice decoding. Simulation results show that the proposed coding schemes outperform existing schemes in terms of outage probabilities in a variety of channel settings, especially when the users-to-relay links are better than the other channel links.

In this paper, we consider secure transmissions in ergodic Rayleigh fast-faded multiple-input multiple-output multiple-antenna-eavesdropper (MIMOME) wiretap channels with only statistical channel state information at the transmitter (CSIT). When the antennas at the legitimate receiver are more than (or equal to) those at the eavesdropper, we prove the first MIMOME secrecy capacity with partial CSIT by establishing a new secrecy capacity upper-bound. The key step is to form an MIMOME degraded channel by dividing the legitimate receiver's channel matrix into two submatrices, and setting one of the submatrices to be the same as the eavesdropper's channel matrix. Next, under the total power constraint over all transmit antennas, we analytically solve the channel-input covariance matrix optimization problem to fully characterize the MIMOME secrecy capacity. Typically, the MIMOME optimization problems are non-concave. However, thanks to the proposed degraded channel, we can transform the stochastic MIMOME optimization problem to be a Schur-concave one and then find its solution. Besides total power constraint, we also investigate the secrecy capacity when the transmitter is subject to the practical per-antenna power constraint. The corresponding optimization problem is even more difficult since it is not Schur-concave. Under the two power constraints considered, the corresponding MIMOME secrecy capacities can both scale with the signal-to-noise ratios (SNR) when the difference between numbers of antennas at legitimate receiver and eavesdropper are large enough. However, when the legitimate receiver and eavesdropper have a single antenna each, such SNR scalings do not exist for both cases.

In this paper we consider the secure transmission with multiple-input, single-output, single-antenna eavesdropper (MISOSE) in fast fading channels where the transmitter knows perfect legitimate channel state information but only the statistics of the eavesdropper's channel. For the MISOSE channels, the artificial noise assisted beamforming proposed by Goel and Negi is a promising technique, where the artificial noise is imposed on the null space of the legitimate channel to disrupt the eavesdropper's reception. Here we propose a generalized artificial noise scheme which allows the injection of the artificial noise to the legitimate channel. Although the generalized artificial noise may cause the leakage of artificial noise at the legitimate receiver, the secrecy rate can still be improved since the covariance matrix of it is more flexible than the heuristic one selected by Goel and Negi. To fully characterize the proposed scheme, we investigate the optimization of its secrecy rate. We first derive the conditions under which the beamformers of the message bearing signal and the generalized artificial noise being the same is optimal. Based on this choice, the complicated secrecy rate optimization problem over the covariance matrices of the message-bearing signal and the generalized artificial noise can be reduced to a much simpler power allocation problem. We also develop an efficient algorithm to solve this non-convex power allocation problem. Numerical results show that our generalized artificial noise scheme outperforms Goel and Negi's heuristic selection, especially in the near eavesdropper settings. In particular, with the aid of the proposed scheme, the regime with non-zero secrecy rate is enlarged, which can significantly improve the connectivity of the network.

Multirelay networks exploit spatial diversity by transmitting user's messages through multiple relay paths. Most works in the literature on cooperative or relay networks assume that all terminals are fully cooperative and neglect the effect of possibly existing malicious relay behaviors. In this work, we consider a multirelay network that consists of both cooperative and malicious relays, and aims to obtain an improved understanding on the optimal behaviors of these two groups of relays via information-theoretic mutual information games. By modeling the set of cooperative relays and the set of malicious relays as two players in a zero-sum game with the maximum achievable rate as the utility, the optimal transmission strategies of both types of relays are derived by identifying the Nash equilibrium of the proposed game. Our main contributions are twofold. First, a generalization to previous works is obtained by allowing malicious relays to either listen or attack in Phase 1 (source-relay transmission phase). This is in contrast to previous works that only allow the malicious relays to listen in Phase 1 and to attack in Phase 2 (relay-destination transmission phase). The latter is shown to be suboptimal in our problem. Second, the impact of CSI knowledge at the destination on the optimal attack strategy that can be adopted by the malicious relays is identified. In particular, for the more practical scenario where the interrelay CSI is unknown at the destination, the constant attack is shown to be optimal as opposed to the commonly considered Gaussian attack.

We consider the secure transmission in ergodic fast Rayleigh fading multiple-input single-output single-antenna-eavesdropper (MISOSE) wiretap channels. We assume that the statistics of both the legitimate and eavesdropper channels are the only available channel state information at the transmitter (CSIT). By introducing a new secrecy capacity upper bound, we prove that the secrecy capacity is achieved by the Gaussian input without prefixing. To attain this result, we form another MISOSE channel for upper-bounding by relaxing the equivocation constraint, and tighten the bound by carefully selecting correlations between the legitimate and eavesdropper channel gains. The resulting upper bound is tighter than the others in the literature which are based on modifying the correlation between the noises at the legitimate receiver and eavesdropper. Next, we fully characterize the secrecy capacity by showing that the optimal channel input covariance matrix is a scaled identity matrix. The key to solve such a stochastic optimization problem is by exploiting the completely monotone property of the secrecy capacity. Finally, we prove that with only statistical CSIT of both channels, the capacity will neither scale with signal-to-noise ratio (SNR) nor the number of antenna. Our numerical results also match these observations and further confirm that having the legitimate CSIT (realizations) is very beneficial to increase the secrecy capacity.

In this paper, we consider the joint design of training and data transmission signals for wiretap channels where the transmitter is to send a secrect massage to the receiver without being intercepted by the eavesdropper. The celebrated secrecy beamforming scheme, which may or may not be assisted by artificial-noise (AN), is adopted in the data transmission phase to achieve this task. The achievable secrecy rate for practical systems with channel estimation error is first derived. Based on the achievable secrecy rate, we find the optimal tradeoff between the energy used for training and data signals. The optimal solutions in the low and high energy regimes are characterized analytically. We show that AN does not provide any advantages in the low energy regime, while it may have significant impact in the high energy regime. Numerical results are presented to verify our theoretical claims.

Wyner-Ziv coding (WZC) is a compression technique using decoder side information, which is unknown at the encoder, to help the reconstruction. In this paper, we propose and implement a new WZC structure, called residual WZC, for the quadratic-Gaussian Wyner-Ziv problem where side information can be arbitrarily distributed. In our two-stage residual WZC, the source is quantized twice and the input of the second stage is the quantization error (residue) of the first stage. The codebook of the first stage quantizer must be simultaneously good for source and channel coding, since it also acts as a channel code at the decoder. Stemming from the non-ideal quantization at the encoder, a problem of channel decoding beyond capacity is identified and solved when we design the practical decoder. Moreover, by using the modified reinforced belief-propagation quantization algorithm, the low-density parity check code (LDPC), whose edge degree is optimized for channel coding, also performs well as a source code. We then implement the residual WZC by an LDPC and a low-density generator matrix code (LDGM). The simulation results show that our practical construction approaches the Wyner-Ziv bound. Compared with previous works, our construction can offer more design flexibility in terms of distribution of side information and practical code rate selection.

In this paper we consider secure transmission for the multiple-input, multiple-output, single-antenna-eavesdropper systems with perfect information of the main channel and only the statistics of the eavesdropper's channel state information known at the transmitter. We adopt the celebrated artificial-noise (AN) assisted beamforming, which was studied by Goel and Negi with the limitation that the AN must be allocated in the null space of the main channel. By removing this limitation, we study the rate optimization problems over the covariance matrices of the signal and the AN. After exploring the structure of the optimal solutions, we show that the original optimization problem can be simplified as a much simpler power allocation problem. Our results show that to improve the rate performance, one may allocate the power of the AN in the directions of the right singular vectors of the main channel. Thus Goel and Negi's AN selection is strictly sub-optimal. Moreover, our simulations show that when the main channel has no null space, the rate performance of our optimized signaling outperforms that of Goel and Negi's significantly.

In this work, we consider an interference-mitigation based cognitive radio system where a secondary transmitter is to communicate with its corresponding receiver without affecting the communication between a primary transmitter-receiver pair. In this case, the secondary transmitter must satisfy a coexistence constraint which requires that no rate degradation occurs at the primary user (PU), even when the latter utilizes only a single-user decoder. To achieve a non-zero rate of the secondary user (SU) under this constraint, Jovicic and Viswanath previously proposed a scheme (referred to as the JV scheme) that utilizes relaying by the secondary transmitter to overcome the interference caused by the simultaneous transmission of the SU's message. In this case, the interference caused by the signals corresponding to PU's message at the secondary receiver (from both the direct and the relay links) is mitigated by employing dirty paper coding (DPC) at the secondary transmitter. However, the interference caused by the SU's message at the primary receiver is not eliminated in this case and, thus, will limit the power (and, hence, the rate) that can be used by the secondary transmitter to transmit its own message. In our work, the use of clean relaying by the secondary transmitter and/or receiver (i.e., relaying without simultaneous transmission of SU's own message) is proposed to improve the quality of the relayed signal and, thereby, increases the rate achievable by the SU. Two improved transmission schemes are proposed: (i) clean relaying by secondary transmitter (CT) and (ii) clean relaying by secondary transmitter and receiver (CTR). The CT scheme utilizes DPC to mitigate interference at the secondary receiver whereas the CTR scheme utilizes coding for multiple access channels with common messages to enable decoding of both PU's and SU's messages at the secondary receiver. The CT scheme can be viewed as a generalization of the JV scheme and, therefore, performs at least as well as the latter. The CTR scheme, on the other hand, is shown to outperform the CT scheme in terms of the multiplexing gain achievable under full channel state information at the transmitter (CSIT) and in terms of the rate achievable with statistical CSIT. Numerical simulations are provided to illustrate these advantages.

Cooperative relaying refers to a technique that allows the source to transmit its messages to the destination via the relaying of multiple cooperative partners and exploits the spatial diversity gains inherent in multiuser wireless systems. In this work, we examine cooperative networks with cooperative and malicious relays and determine the optimal behavior for both kinds of relays using a game-theoretic approach. We formulate the problem as a zero-sum game, determining the optimal relay strategies by identifying the Nash equilibrium of the proposed game under individual power constraints. We prove, with Rayleigh fading, the optimal strategy for malicious relays is to transmit independent Gaussian noise using full power at each relay and for cooperative relays is to independently re-encode the source's message into Gaussian signals and forward them to the destination. Inter-cooperation among relays is unnecessary. The results are verified through numerical simulations.

We consider secure transmission in fading channels with only the statistics of the eavesdropper's channel state information known at the transmitter. We optimize the celebrated artificial-noise (AN) assisted beamforming, which was studied by Goel and Negi using heuristically selected AN and beamforming directions. We find that Goel and Negi's AN selection is strictly sub-optimal. On the contrary, one may inject AN to the beam direction of the message to improve the secrecy rate performance. We prove that for a multiple-input, single-output, single-antenna-eavesdropper system, the optimal transmission scheme is a beamformer which is aligned to the direction of the legitimate channel. We then prove that, for the part of the AN in the null space of the legitimate channel, uniform power allocation is optimal. We also provide the necessary condition for the proposed AN selection to be optimal. Simulation results show that our AN selection outperforms Goel and Negi's, especially when the legitimate user's channel quality is poor. In particular, when AN assisted beamforming is applied, the region with non-zero secrecy rate is enlarged, which can significantly improve the connectivity of secure networks.

Linear-assignment Gel'fand-Pinsker coding (LA-GPC) is a coding technique for channels with interference known only at the transmitter, where the known interference is treated as side-information (SI). As a special case of the LA-GPC, dirty paper coding has been shown to be able to achieve the optimal interference-free rate for SI channels with perfect channel state information at the transmitter (CSIT). In the cases where only the channel distribution information at the transmitter (CDIT) is available, LA-GPC also has good (sometimes optimal) performance in a variety of fast and slow fading SI channels. In this letter, we design filters in the nested lattice based coding to make it achieve the same rate performance as the LA-GPC in multiple-input multiple-output (MIMO) channels. Compared with the random Gaussian codebooks used in previous works, our resultant coding schemes have algebraic structures and can be implemented in practical systems. Simulations in slow-fading channels are provided, and near interference-free error performance is obtained. The proposed coding schemes can serve as the fundamental building blocks to achieve the promised rate performance of MIMO Gaussian broadcast channels with CDIT or perfect CSIT.

The impact of quantized channel direction information (CDI) on the achievable secrecy rate is studied for multiple antenna wiretap channels. By assuming that the eavesdropper's channel is unknown at the transmitter, we adopt the transmission scheme where artificial noise (AN) is imposed in the null space of the legitimate receiver's channel to disrupt the eavesdropper's reception. It has been shown that, in the ideal case where perfect CDI is available at the transmitter, the achievable secrecy rate can be made arbitrarily large by increasing the transmission power. However, when only quantized CDI is available, the AN that was originally intended to jam the eavesdropper may now leak into the legitimate receiver's channel, causing significant secrecy rate loss. For a given number of feedback bits B and transmission power P, we derive the optimal power allocation among the message-bearing signal and the AN to maximize the secrecy rate under AN leakage. We show that, when B is sufficiently large, one should allocate power evenly among the message-bearing signal and the AN; whereas when B is small, one should be more conservative in allocating power to the AN. Moreover, by showing that the achievable secrecy rate under quantized CDI is bounded by a constant, we derive a scaling law between B and P that is necessary to maintain a constant secrecy rate loss compared to the perfect CDI case. The scaling of B is shown to be logarithmic of P. These results are first derived for the multiple-input single-output single-antenna-eavesdropper scenario and are later extended to the multiple-input multiple-output multiple-antenna-eavesdropper case. Numerical simulations are provided to verify our theoretical claims.

In this work, we examine the impact of quantized channel direction feedback on the achievable secrecy rate of multiple-antenna wiretap channels. To guarantee secrecy without knowledge of the eavesdropper's channel, we consider the transmission scheme proposed by Goel and Negi where artificial noise (AN) is imposed in the null space of the legitimate receiver's channel to disrupt the eavesdropper's reception. When perfect knowledge of the legitimate receiver's channel direction information (CDI) is available at the transmitter, the secrecy rate can be made arbitrarily large by increasing the transmission power. However, perfect CDI is difficult to achieve in practice due to rate-limitations on the feedback channel. When only quantized CDI is available at the transmitter, the AN that is only intended to disrupt the eavesdropper's reception may leak into the legitimate receiver's channel, causing significant loss in secrecy rate. In fact, we show that the achievable secrecy rate under quantized CDI is bounded by a constant even as the transmission power increases. To guarantee a constant rate loss compared to the perfect CDI case, we show that the number of feedback bits must scale at least logarithmically with the transmission power. These theoretical claims are verified by computer simulations.

In this paper, we present the design of cognitive radio in the Rician channel with partial channel state information at the transmitter (CSIT). We replace the dirty paper coding (DPC) used in the cognitive radio with full CSIT by the linear assignment Gel'fand-Pinsker coding (LA-GPC) which can achieve better error performance when there is only partial CSIT. Based on the achievable rate derived from the LA-GPC, two optimization problems under the fast and slow fading channels are formulated. We derive semi-analytical solutions to find the relaying ratios and precoding coefficients. We also show that the parameters derived by the proposed methods converge to the optimal full CSIT solutions in the asymptotic cases. This result verifies the correctness of the proposed methods asymptotically. Moreover, a new coding scheme is proposed to implement the LA-GPC in practice. Simulation results show that the proposed semi-analytical solutions perform close to the optimal solutions found by brute-force search, and outperform the systems based on naive DPC. Simulation results also show that the proposed practical coding scheme can effectively approach the theoretical rate performance.

We propose an algorithm which iteratively computes the transmit-receive beamforming filters and the power allocation matrix to solve the multiuser multi-input multi-output (MIMO) downlink beamforming problem under signal-to-interference- plus-noise-ratio (SINR) constraints. The transmitter is a multi- antenna base-station broadcasting to users. Each user has multiple antennas at the receiver. The beamforming filter is a group maximum SINR filter which exploits intra-group cooperation, and the power allocated to each data stream is adjusted to enhance performance. Simulation results verify the superiority of the proposed algorithm over previous works.

Wyner-Ziv coding (WZC) is a compression technique which uses decoder side-information to help reconstruction. We present a new coding structure using two-stage successive quantization with two codebooks to solve the Wyner-Ziv problem in the quadratic Gaussian case. The optimal Wyner-Ziv bound is proved to be achievable by random coding analysis. Compared to the existing nested-lattice based design approaches, the two component codes in our construction can be designed independently, which simplifies the code design significantly. Moreover, besides the original noiseless setting where the source is directly observed by the encoder, our coding also suits for the noisy WZC problem where the source is observed via a noisy memoryless channel.

This paper adopts an information-theoretic framework for the design of collusion-resistant coding/decoding schemes for digital fingerprinting. More specifically, the minimum distance decision rule is used to identify 1 out oftpirates. Achievable rates, under this detection rule, are characterized in two scenarios. First, we consider the averaging attack where a random coding argument is used to show that the rate 1/2 is achievable witht=2 pirates. Our study is then extended to the general case of arbitrarythighlighting the underlying complexity-performance tradeoff. Overall, these results establish the significant performance gains offered by minimum distance decoding compared to other approaches based on orthogonal codes and correlation detectors which can support only a subexponential number of users (i.e., a zero rate). In the second scenario, we characterize the achievable rates, with minimum distance decoding, under any collusion attack that satisfies the marking assumption. Fort=2 pirates, we show that the rate 1-H(0.25) ap 0.188 is achievable using an ensemble of random linear codes. Fortges 3, the existence of a nonresolvable collusion attack, with minimum distance decoding, for any nonzero rate is established. Inspired by our theoretical analysis, we then construct coding/decoding schemes for fingerprinting based on the celebrated belief-propagation framework. Using an explicit repeat-accumulate code, we obtain a vanishingly small probability of misidentification at rate 1/3 under averaging attack witht=2. For collusion attacks, which satisfy the marking assumption, we use a more sophisticated accumulate repeat accumulate code to obtain a vanishingly small misidentification probability at rate 1/9 witht=2. These results represent a marked improvement over the best available designs in the literature.

Cognitive radio (CR) has been proposed as an efficient method to reuse the licensed spectrum. It recognizes the primary (licensed) users' signals and adapts its own to minimize the interference it generates. When perfect channel state information is known at the transmitters, the capacity of CR system can be achieved by utilizing the dirty paper coding (DPC). In this paper, we consider the performance of the CR system under both fast and slow fading channels with only channel statistics known at the transmitters. Due to the limited channel state information, the original DPC fails and is replaced by the so-called linear-assignment Gel'fand-Pinsker coding. By carefully designing the parameters based on this preceding, this system has significant rate gains over naively treating primary users' signals as interference for fast and slow fading scenarios.

In this paper we aim to solve the multiuser multi- input multi-output (MIMO) downlink beamforming problem. The transmitter is a multi-antenna base-station broadcasting to users. Each user has multiple antennas at the receiver. A solution of the joint transmit-receive beamforming and power allocation under signal-to-interference-plus-noise-ratio (SINR) constraints in this system is proposed. The beamforming filter is a group maximum SINR filter which exploits intra-group cooperation. Taking advantage of the uplink-downlink duality property, the proposed algorithm iteratively computes the transmit-receive beamforming filters and the power allocation matrix. Simulation results verify the superiority of the proposed algorithm over previous works using per stream maximum SINR method.

Recently, the vector dirty paper coding (DPC) achievable rate region has been shown to be the capacity region of a multiple-input multiple-output Gaussian broadcast channel (MIMO GBC). With DPC, the multiuser interference noncausally known at the transmitter can be completely removed. In this paper, we present a vector DPC structure for MIMO GBC. It is a generalization of the single antenna superposition dirty paper coding for the scalar Gaussian dirty paper problem proposed by Bennatan et al. In a theoretical random code setting, this construction is shown to be able to achieve the promised rate performance of the MIMO GBC. We also implement it with existing vector quantizer and capacity-achieving channel coding. Combined with iterative decoding, a design example validates the effectiveness of our methods.

In this paper, we improve the peak to average power ratio (PAPR) reduction scheme for multicarrier systems proposed by Collings and Clarkson by applying dirty paper coding with peak power constraint. We compare the bit error rate (BER) performance among conventional orthogonal frequency division multiplexing (OFDM), Collings and Clarkson’s method, and our proposed scheme with bit loading. From simulation we find that when channel coding is considered, Collings and Clarkson’s method is the worst independent of the number of bits loaded. The proposed method performs the best when the number of bits is large and hence is suitable for high speed transmission.