Incomplete multiview clustering is of high recent interest, fueled by the advancement of common information-based deep multiview learning. The practical scenarios where unpaired multiview data with missing values have wide applications in generative learning, cross-modal retrieval, and wireless device identification problems. Following the perspective that the shared information between the incomplete multiview data aligns with the cluster targets, recent works have generalized the well-known common information frameworks in information theory multiview learning problems, with improved performance reported. Different from previous works, we extend the frameworks to incomplete multiview clustering problems and propose an efficient solver: Wyner Incomplete MultiView Clustering (WyIMVC). Interestingly, the common randomness in WyIMVC allows for joint clustering and missing value inference in contrast to the compared methods in the literature. Moreover, leveraging the difference-of-convex structure of the formulated problems, we propose an efficient solver with a convergence guarantee independent of initialization. Empirically, our solver outperforms the state-of-the-art solvers in a range of incomplete multiview datasets with varying numbers of views and dimensions.

In this work, we propose computationally efficient solvers for novel extensions of Wyner common information. By separating information sources into bipartite, the proposed Bipartite common information framework has difference-of-convex structure for efficient non-convex optimization. In known joint distribution cases, our difference-of-convex algorithm(DCA)-based solver has a provable convergence guarantee to local stationary points. As for unknown distribution settings, the insights from DCA combined with the exponential family of distributions for parameterization allows for closed-form expressions for efficient estimation. Furthermore, we show that the Bipartite common information applies to multi-modal clustering without employing ad-hoc clustering algorithms. Empirically, our solvers outperform state-of-the-art methods in clustering accuracy and running time over a range of non-trivial multi-modal clustering datasets with different number of data modalities.

This paper's primary focus is on designing short parallel concatenated coding schemes and list-based decoding algorithms with low complexity. We aim to design a code with a relatively large minimum Hamming distance that can be efficiently decoded through list decoding. To achieve this, we introduce a novel parallel concatenated coding scheme, where the two constituent codes are linked by a full-rank matrix instead of the interleaver, which is commonly used in Turbo codes. The proposed code structures enable us to develop codes with significantly improved minimum Hamming distances. We also demonstrate that by utilizing a convolutional code as one of the constituent codes, we can effectively employ the parallel list Viterbi algorithm to generate a list of candidate codewords. Then, we select the candidate with the lowest Euclidean distance to the overall received signal. This allows us to use a highly complex constituent code, with potentially large minimum Hamming distance, as the second constituent code without increasing the decoding complexity. Simulation results validate the superior performance of these coding schemes compared to existing candidate coding schemes for short packet communications, particularly at very low rates.

Wireless fingerprinting is a device identification approach which leverages hardware imperfections and wireless channel variations as unique user-centric signatures. Recent studies have also demonstrated that user behavior can be used as a signature by collecting network traffic data, e.g., packet length, without the need to decode/decrypt the payload. Inspired by these results, we propose a multi-layer fingerprinting framework that jointly combines the multi-layer signatures for improved identification performance. In contrast to previous works in the area, our multi-view learning approach is rooted in the common information framework developed by Wyner [1] and is able to exploit data with multiple forms to enable the extraction of the user-centric signatures shared among the multi-layer features without the need for labels (i.e., unsupervised learning setup). We further use variational inference to obtain a computationally efficient algorithm based on a tight surrogate bound on the loss function. Our evaluation framework is based on a dataset obtained by combining real-world video traffic with simulated physical layer characteristics. Finally, our empirical results show that our Wyner Variational Autoencoder significantly outper-forms the state-of-the-art baseline in the unsupervised wireless fingerprinting setting.

In this work, we adopt Wyner common information framework for unsupervised multi-view representation learning. Within this framework, we propose two novel formulations that enable the development of computational efficient solvers based on the alternating minimization principle. The first formulation, referred to as the variational form, enjoys a linearly growing complexity with the number of views and is based on a variational-inference tight surrogate bound coupled with a Lagrangian optimization objective function. The second formulation, i.e., the representational form, is shown to include known results as special cases. Here, we develop a tailored version from the alternating direction method of multipliers (ADMM) algorithm for solving the resulting non-convex optimization problem. In the two cases, the convergence of the proposed solvers is established in certain relevant regimes. Furthermore, our empirical results demonstrate the effectiveness of the proposed methods as compared with the state-of-the-art solvers. In a nutshell, the proposed solvers offer computational efficiency, theoretical convergence guarantees (local minima), scalable complexity with the number of views, and exceptional accuracy as compared with the state-of-the-art techniques. Our focus here is devoted to the discrete case and our results for continuous distributions are reported elsewhere.

In this work, we propose solving the Information Bottleneck (IB) and Privacy Funnel (PF) problems with Douglas-Rachford Splitting methods (DRS). We study a general Markovian information-theoretic Lagrangian that includes IB and PF into a unified framework. We prove the linear convergence of the proposed solvers using the Kurdyka- ojasiewicz inequality. Moreover, our analysis is beyond IB and PF and applies to any convex-weakly convex pair objectives. Based on the results, we develop two types of linearly convergent IB solvers, with one improves the performance of convergence over existing solvers while the other can be independent to the relevance-compression trade-off. Moreover, our results apply to PF, yielding a new class of linearly convergent PF solvers. Empirically, the proposed IB solvers IB obtain solutions that are comparable to the Blahut-Arimoto-based benchmark and is convergent for a wider range of the penalty coefficients than existing solvers. For PF, our non-greedy solvers can characterize the privacy-utility trade-off better than the clustering-based greedy solvers.

In this work, we generalize the information bottleneck (IB) approach to the multi-view learning context. The exponentially growing complexity of the optimal representation motivates the development of two novel formulations with more favorable performance-complexity tradeoffs. The first approach is based on forming a stochastic consensus and is suited for scenarios with significant representation overlap between the different views. The second method, relying on incremental updates, is tailored for the other extreme scenario with minimal representation overlap. In both cases, we extend our earlier work on the alternating directional methods of multiplier (ADMM) solver and establish its convergence and scalability. Empirically, we find that the proposed methods outperform state-of-the-art approaches in multi-view classification problems under a broad range of modelling parameters.

Coded caching techniques have received significant attention lately due to their provable gains in reducing the cost of data delivery in wireless networks. These gains, however, have only been demonstrated under the assumption of a free placement phase. This unrealistic assumption poses a significant limitation, especially in cases where aggressive placement strategies can lead to a significant transmission cost that may even be higher than the corresponding cost of the delivery phase. In this paper, we relax this assumption and propose a general caching framework that captures the transmission cost of the two phases, and hence, results in minimizing the overall rate of the caching network. We model the dynamic nature of the network through a cost structure that allows for varying the network architecture and cost per transmission, across the placement and delivery phases. We start with the scenario where the individual users have no limit on the available caching memory and characterize the jointly optimal solution as a function of the different parameters in our cost structure. Then, we characterize the effect of memory constraints on the optimal solution in certain special cases. Interestingly, our results identify regions where the uncoded caching scheme outperforms its coded counterpart. Further, coded caching is shown to offer performance gains only when the network architecture during the placement phase is different from that during the delivery phase.

Compound MIMO wiretap channel with double sided uncertainty is considered under channel mean information model. In mean information model, channel variations are centered around its mean value which is fed back to the transmitter. We show that the worst case main channel is anti-parallel to the channel mean information resulting in an overall unit rank channel. Further, the worst eavesdropper channel is shown to be isotropic around its mean information. Accordingly, we provide the capacity achieving beamforming direction. We show that the saddle point property holds under mean information model and, thus, compound secrecy capacity equals to the worst case capacity over the class of uncertainty. Moreover, capacity achieving beamforming direction is found to require matrix inversion, thus, we derive null steering (NS) beamforming as an alternative sub-optimal solution that precludes the necessity of matrix inversion. NS beamformer is the beamforming direction orthogonal to the eavesdropper mean channel that maintains the maximum possible gain in the direction mean main channel. Extensive computer simulation reveals that NS beamforming performs very close to the optimal solution. It also verifies that, NS beamforming outperforms both maximum ratio transmission (MRT) and zero forcing (ZF) beamforming approaches over the entire SNR range. Finally, an equivalence relation with MIMO wiretap channel in Rician fading environment is established.

The mismatch between user demand and service supply creates a congestion in mobile wireless networks. The literature has a strong evidence that user behavior is highly predictable. Taking advantage of user demand predictability allows the carrier to apply proactive caching in order to smooth out the network load. Moreover, harnessing the information about user mobility enhances carrier's caching decision and minimizes the incurred service cost. The information about users' trajectories allows the carrier to predict their availability in some popular locations which experience high demand. Finding an optimal caching strategy alleviates the network congestion in these locations and improves the overall network performance. We introduce a system model where the carrier takes a decision to proactively cache some of the requested data items in users' devices. Users are equipped with D2D communication which is used to share cached data items between them in these popular locations. Users get reward to compensate their memory usage and battery consumption. Although caching helps users to save some of their payment, this reward promotes them to participate in the proposed model. We establish a lower bound on the proactive service cost which yields some insights on how user demand and mobility statistics affect carrier's caching decision.

In this work, we formulate and study the profit maximization problem for a wireless service provider (SP) that encounters time-varying, yet partially predictable, demand characteristics. The disparate demand levels throughout the course of the day yield excessive service cost in the peak hour that substantially hurts the reaped profit. With the SP's ability to track and statistically predict future requests of its users, we propose to enable proactive caching of the peak hour demand ahead during off-peak times. Thus, network traffic will be smoothed out, while end-users' activity patterns are undisturbed. In addition, the SP is able to assign personalized pricing policies that strike the best balance between enhancing the certainty about the future demand for optimal proactive caching and maximizing the revenue collected from end-users. Comparing the proposed system's performance to the baseline scenario of the existing practice of no-proactive service, we show that the SP attains profit gain that grows with number of users, at least, as the first derivative of the cost function. Moreover, end-users that receive proactive caching services make strictly positive savings. Thus, we essentially demonstrate the win-win situation to be reaped through the exploitation of the consistent users' activity.

Abstract In this paper, we derive the capacity of the deterministic relay networks with relay messages. We consider a network that consists of five nodes, four of which can only communicate via the fifth one. However, the fifth node is not merely a relay as it may exchange private messages with the other network nodes. First, we develop an upper bound on the capacity region based on the notion of a single‐sided genie. In the course of the achievability proof, we also derive the deterministic capacity of a four‐user relay network (without private messages at the relay). The capacity achieving schemes use a combination of two network coding techniques: the simple ordering scheme and detour scheme. In the simple ordering scheme, we order the transmitted bits at each user such that the bi‐directional messages will be received at the same channel level at the relay, while the basic idea behind the detour scheme is that some parts of the message follow an indirect paths to their respective destinations. This paper, therefore, serves to show that user cooperation and network coding can enhance throughput, even when the users are not directly connected to each other. Finally, we make a conjecture about the capacity region of the generalK‐node relay network with relay messages. Copyright © 2016 John Wiley & Sons, Ltd.

In this paper, the interactions between a wireless network carrier and a set of end-users trading data contents that were downloaded proactively are studied. In particular, we investigate the profit maximization problem for wireless network carrier and payment minimization for end-users. Motivated by recent findings on proactive resource allocation, we focus on the scenario whereby end-users harness their predictable demands and the possibility of being connected together in downloading proactive data and selling them again to minimize their expected payments. The carrier, on the other hand, takes a commission from each trade and utilizes smart pricing schemes to differentiate between off-peak and peak hour prices to spreadout the peak load and maximize its profit. A marketplace based on risk sharing concept is achieved where the tension between carrier and end-users and the competition between end-users themselves is formulated as a Stackelberg game. The existence and uniqueness of the non-cooperative sub-game Nash equilibrium is shown. We compare the new equilibria with the baseline scenario of smart pricing proactive model without trading between users. Despite the uncertainty about future demand, and the freshness of proactively downloaded contents, we characterize new equilibria point that yield to a win-win situation with respect to the baseline equilibrium. We show that users' activity patterns can be harnessed to create a marketplace that will maximize the carrier's profit while users pay less.

In this paper, we propose and study optimal proactive resource allocation and demand shaping for data networks. Motivated by the recent findings on the predictability of human behavior patterns in data networks, and the emergence of highly capable handheld devices, our design aims to smooth out the network traffic over time and minimize the data delivery costs. Our framework utilizes proactive data services as well as smart content recommendation schemes for shaping the demand. Proactive data services take place during the off-peak hours based on a statistical prediction of a demand profile for each user, whereas smart content recommendation assigns modified valuations to data items so as to render the users' demand less uncertain. Hence, our recommendation scheme aims to boost the performance of proactive services within the allowed flexibility of user requirements. We conduct theoretical performance analysis that quantifies the leveraged cost reduction through the proposed framework. We show that the cost reduction scales at the same rate as the cost function scales with the number of users. Furthermore, we prove that demand shaping through smart recommendation strictly reduces the incurred cost even below that of proactive downloads without recommendation.

The global adoption of smart phones has raised major concerns about a potential surge in the wireless traffic due to the excessive demand on multimedia services. This ever increasing demand is projected to cause significant congestions and degrade the quality of service for network users. In this paper, we develop a proactive caching framework that utilizes the predictability of the mobile user behavior to offload predictable traffic through the WiFi networks ahead of time. First, we formulate the proactive scheduling problem with the objective of maximizing the user-content hit ratio subject to constrains stemming from the user behavioral models. Second, we propose a quadratic-complexity (in the number of slots per day) greedy, yet, high performance heuristic algorithm that pinpoints the best download slot for each content item to attain maximal hit ratio. We confirm the merits of the proposed scheme based on the traces of a real dataset leveraging a large number of smart phone users who consistently utilized our framework for two months.

In this paper, we study the degrees of freedom (DoF) of the MIMO relay networks. We start with a general Y channel, where each user has Miantennas and aims to exchange messages with the other two users via a relay equipped with N antennas. Then, we extend our work to a general 4-user MIMO relay network. Unlike most previous work which focused on the total DoF of the network, our aim here is to characterize the achievable DoF region as well. We develop an outer bound on the DoF region based on the notion of one sided genie. Then, we define a new achievable region using the Signal Space Alignment (SSA) and the Detour Schemes. Our achievable scheme achieves the upper bound for certain conditions relating Mi's and N.

In this work, we investigate the profit maximization problem for wireless network carriers and payment minimization for end users. Motivated by our recent findings on proactive resource allocation, we focus on the scenario whereby end users harness predictable demand and WiFi connectivity in proactive data downloads, to minimize their expected payments. Carriers, on the other hand, utilize smart pricing schemes to differentiate between the off-peak and peak hour prices so as to reduce peak costs and maximize their profit.We formulate the tension between the carrier and end user as a two-player Stackelberg game in which the carrier assigns prices first, then the end user responds with optimized proactive downloads. We explore the equilibrium points under maximum and average price constraints, and study the impact of WiFi availability on the system's performance. In particular, we compare the new equilibria with the baseline scenario of flat pricing and no proactive downloads. Despite the potential uncertainty about future demand, and the freshness of proactively downloaded content, we characterize new equilibria points that yield win-win situation with respect to the baseline equilibrium.

Recent studies have shown that retransmissions can cause heavy-tailed transmission delays even when packet sizes are light tailed. In addition, the impact of heavy-tailed delays persists even when packets size are upper bounded. The key question we study in this paper is how the use of coding techniques to transmit information, together with different system configurations, would affect the distribution of delay. To investigate this problem, we model the underlying channel as a Markov modulated binary erasure channel, where transmitted bits are either received successfully or erased. Erasure codes are used to encode information prior to transmission, which ensures that a fixed fraction of the bits in the codeword can lead to successful decoding. We use incremental redundancy codes, where the codeword is divided into codeword trunks and these trunks are transmitted one at a time to provide incremental redundancies to the receiver until the information is recovered. We characterize the distribution of delay under two different scenarios: 1) decoder uses memory to cache all previously successfully received bits and 2) decoder does not use memory, where received bits are discarded if the corresponding information cannot be decoded. In both cases, we consider codeword length with infinite and finite support. From a theoretical perspective, our results provide a benchmark to quantify the tradeoff between system complexity and the distribution of delay.

We address the question of optimal proactive service and demand shaping for content distribution in data networks through smart pricing. We develop a proactive download scheme that utilizes the probabilistic predictability of the human demand by proactively serving potential users' future requests during the off-peak times. Thus, it smooths-out the network traffic and minimizes the time average cost of service. Moreover, we incorporate the varying economic responsiveness and demand flexibilities of users into our model to develop a demand shaping mechanism that further improves the gains of proactive downloads. To that end, we propose a model that captures the uncertainty about the users' demand as well as their responsiveness to the pricing employed by the service providers. We propose a joint proactive resource allocation and demand shaping scheme based on nonconvex optimization algorithms, and show that it always leads to strictly better performance over its proactive counterpart without demand shaping.

We consider information theoretic secrecy over flat fading channels under relaxed delay constraints. More specifically, we extend the definition of outage secrecy capacity for single-input single-output single-eavesdropper case (SISOSE) to account for relaxed delay constraints, and study the fundamental limits under two different assumptions on the transmitter CSI (channel state information). First, we provide bounds on secrecy outage capacity with k+1 block delay constraint. We show that the bounds are tight for several special cases. We also provide a weaker lower bound that is easier to compute, and show that under low SNR, delay constraint has significant impact on secrecy outage capacity. The analysis serves as an important step towards complete characterization of information theoretic security with delay and outage constraints.

We study the bounds and means of optimal caching in overlay Content Distribution Networks (CDN) that serve data with dynamic content to end-users who send random requests for the most up-to-date version of such content. Applications with such dynamic content are numerous, including daily news, weather conditions, stock market prices, social networking messages, etc. The service for such a dynamically changing content necessitates a fundamentally different approach than traditional pull-based (also called non-proactive) schemes. In particular, proactive caching is required to optimize the type and amount of content to be updated in the local servers of a CDN hence minimize the transmission and caching costs, subject to storage constraints. We study the metric of cost reduction achieved by proactive caching over non-proactive caching strategies. We introduce the notion of popularity to establish fundamental upper and lower bounds on cost reduction under different degrees of storage space constraints. We prove the lower bounds to achieve the optimal rate of increase achieved by the upper bounds as the database of items increases. In particular, for a general form of convex, superlinear and monotonically increasing cost functions, our results reveal that the optimal cost reduction scales as the cost function itself, or at least as its first derivative, depending on the number of popular data items, as well as the cache storage capacity.

In this paper, we completely characterize the deterministic capacity region of a four-node relay network with no direct links between the nodes, where each node communicates with the three other nodes via a relay. Towards this end, we develop an upper bound on the deterministic capacity region, based on the notion of a one-sided genie. To establish achievability, we use the detour schemes that achieve the upper bound by routing specific bits via indirect paths instead of sending them directly.

We study the capacity region of a deterministic 4-node network, where 3 nodes can only communicate via the fourth one. However, the fourth node is not merely a relay since it can exchange private messages with all other nodes. This situation resembles the case where a base station relays messages between users and delivers messages between the backbone system and the users. We assume an asymmetric scenario where the channel between any two nodes is not reciprocal. First, an upper bound on the capacity region is obtained based on the notion of single sided genie. Subsequently, we construct an achievable scheme that achieves this upper bound using a superposition of broadcasting node 4 messages and an achievable “detour” scheme for a reduced 3-user relay network.

No abstract available.

We investigate the delay limited secrecy capacity of the flat fading channel under two different assumptions on the available transmitter channel state information (CSI). The first scenario assumes perfect prior knowledge of both the main and eavesdropper channel gains. Here, upper and lower bounds on the delay limited secrecy capacity are derived, and shown to be tight in the high signal-to-noise ratio (SNR) regime. In the second scenario, only the main channel CSI is assumed to be available at the transmitter where, remarkably, we establish the achievability of a non-zero delay-limited secure rate, for a wide class of channel distributions, with a high probability. In the two cases, our achievability arguments are based on a novel two-stage key-sharing approach that overcomes the secrecy outage phenomenon observed in earlier works.

This paper considers point-to-point secure communication over flat fading channels under an outage constraint. More specifically, we extend the definition of outage capacity to account for the secrecy constraint and obtain sharp characterizations of the corresponding fundamental limits under two different assumptions on the transmitter channel state information (CSI). First, we find the outage secrecy capacity assuming that the transmitter has perfect knowledge of the legitimate and eavesdropper channel gains. In this scenario, the capacity achieving scheme relies on opportunistically exchanging private keys between the legitimate nodes. These keys are stored in a key buffer and later used to secure delay sensitive data using the Vernam's one time pad technique. We then extend our results to the more practical scenario where the transmitter is assumed to know only the legitimate channel gain. Here, our achievability arguments rely on privacy amplification techniques to generate secret key bits. In the two cases, we also characterize the optimal power control policies which, interestingly, turn out to be a judicious combination of channel inversion and the optimal ergodic strategy. Finally, we analyze the effect of key buffer overflow on the overall outage probability.

The two-way wiretap channel is considered in this paper. Two legitimate users, Alice and Bob, wish to exchange messages securely in the presence of a passive eavesdropper Eve. In the full-duplex scenario, where each node can transmit and receive simultaneously, new achievable secrecy rate regions are obtained based on the idea of allowing the two users to jointly optimize their channel prefixing distributions and binning codebooks in addition to key sharing. The new regions are shown to be strictly larger than the known ones for a wide class of discrete memoryless and Gaussian channels. In the half-duplex case, where a user can only transmit or receive on any given degree of freedom, the idea of randomized scheduling is introduced and shown to offer a significant gain in terms of the achievable secrecy sum-rate. A practical setup is further developed based on a near field wireless communication scenario, and it is shown that one can exploit the two-way nature of the communication, via appropriately randomizing the transmit power levels and transmission schedule, to introduce significant ambiguity at a noiseless Eve.

This paper introduces the novel concept of proactive resource allocation for wireless networks, through which the predictability of user behavior is exploited to balance the wireless traffic over time, and significantly reduces the bandwidth required to achieve a given blocking/outage probability. We start with a simple model in which smart wireless devices are assumed to predict the arrival of new requests and submit them to the network$T$time slots in advance. Using tools from large deviation theory, we quantify the resulting prediction diversity gain to establish that the decay rate of the outage event probabilities increases with the prediction duration$T$. Remarkably, we also show that, in the cognitive networking scenario, the appropriate use of proactive resource allocation by primary users improves the diversity gain of the secondary network at no cost in the primary network diversity. We also shed light on multicasting with predictable demands and show that proactive multicast networks can achieve a significantly higher diversity gain that scales superlinearly with$T$. Finally, we conclude by a discussion of the new research questions posed under the umbrella of the proposed proactive wireless resource framework.

In this work, we analyze the diversity gain region (DGR) of the single-antenna Rayleigh fading Z-Interference channel (ZIC). More specifically, we characterize the achievable DGR of the fixed-power split Han-Kobayashi (HK) approach under these assumptions. Our characterization comes in a closed form and demonstrates that the HK scheme with only a common message is a singular case, which achieves the best DGR among all HK schemes for certain multiplexing gains. Finally, we show that generalized time sharing, with variable rate and power assignments for the common and private messages, does not improve the achievable DGR.

We characterize the achievable three-dimensional tradeoff between diversity, multiplexing, and delay of the single antenna Automatic Retransmission reQuest (ARQ) Z-interference channel. Non-cooperative and cooperative ARQ protocols are adopted under these assumptions. Considering no cooperation exists, we study the achievable tradeoff of the fixed-power split Han-Kobayashi (HK) approach. Interestingly, we demonstrate that if the second user transmits the common part only of its message in the event of its successful decoding and a decoding failure at the first user, communication is improved over that achieved by keeping or stopping the transmission of both the common and private messages. Under cooperation, two special cases of the HK are considered for static and dynamic decoders. The difference between the two decoders lies in the ability of the latter to dynamically choose which HK special-case decoding to apply. Cooperation is shown to dramatically increase the achievable first user diversity.

Achieving information theoretic security with practical coding complexity is of definite interest. This work first focuses on the key agreement problem. For this problem, a new cross-layer secure coding protocol over block fading channels is proposed. The proposed scheme requires only the statistical knowledge about the eavesdropper channel state information (CSI), and, utilizing a privacy amplification technique, reduces the problem of key agreement to a provably secure coding problem per block. Focusing on this secure coding problem, it is shown that polar codes, introduced by Arikan, achieve nonzero perfect secrecy rates for the binary-input degraded wiretap channel while enjoying a remarkably low encoding-decoding complexity. We further show that, in the special case of symmetric main and eavesdropper channels, this coding technique achieves the secrecy capacity. This approach is also extended to the multiple-access channel with a degraded eavesdropper where a nontrivial achievable secrecy region is established. This polar coding method is then utilized in the proposed key agreement protocol, where the secure coding per block is used to create an advantage for the legitimate nodes over the eavesdropper, which is then turned into a private key via the privacy amplification module.

This paper studies the achievable secure rate per source-destination pair in wireless networks. First, a path loss model is considered, where the legitimate and eavesdropper nodes are assumed to be placed according to Poisson point processes with intensities λ and λe, respectively. It is shown that, as long as λe/λ =o((logn)-2), almost all of the nodes achieve a perfectly secure rate of Ω(1/√n) for the extended and dense network models. Therefore, under these assumptions, securing the network does not entail a loss in the per-node throughput. The achievability argument is based on a novel multihop forwarding scheme where randomization is added in every hop to ensure maximal ambiguity at the eavesdropper(s). Second, an ergodic fading model withnsource-destination pairs and neeavesdroppers is considered. Employing the ergodic interference alignment scheme with an appropriate secrecy precoding, each user is shown to achieve a constant positive secret rate for sufficiently largen. Remarkably, the scheme does not require eavesdropper CSI (only the statistical knowledge is assumed) and the secure throughput per node increases as we add more legitimate users to the network in this setting. Finally, the effect of eavesdropper collusion on the performance of the proposed schemes is characterized.

Recent work has shown that retransmissions can cause heavy-tailed transmission delays even when packet sizes are light-tailed. Moreover, the impact of heavy tailed delays persist even when packets are of finite size. The key question we study in this paper is how the use of coding techniques to transmit information could mitigate delays. To investigate this problem, we consider an important communication channel called the Binary Erasure Channel, where transmitted bits are either received successfully or lost (called an erasure). This model is a good abstraction of not only the wireless channel but also the higher layer link, where erasure errors can happen. Many coding schemes, known as erasure codes, have been designed for this channel. Specifically, we focus on the fixed rate coding scheme, where decoding is said to be successful if a certain fraction β of the codeword is received correctly. We study two different scenarios: (I) A codeword of length Lcis retransmitted as a unit until the receiver successfully receives more than βLcbits in the last transmission. (II) All successfully received bits from every (re)transmissions are buffered at the receiver according to their positions in the codeword, and the transmission completes once the received bits become decodable for the first time. Our studies reveal that complicated and surprising relationships exist between the coding complexity and the transmission delay/throughput. From a theoretical perspective, our results provide a benchmark to quantify the tradeoffs between coding complexity and transmission throughput for receivers that use memory to buffer (re)transmissions until success and those that do not buffer intermediate transmissions.

A coding problem, over a slotted system, is introduced where the sender has to transmit one out of several packets to the receiver, but learns the request only at the beginning of each slot with prior statistical information about which packet is needed at the receiver. There is an associated cost of sending bits at each slot, and the goal is to minimize the expected cost of the communication. A proactive coding scheme is proposed, where the source proactively communicates with the receiver before the receiver requests the message. This way, by designing a cost optimal side information at the receiver, the scheme is able to minimize the expected cost of the communication. Numerical results are provided demonstrating the gains obtained by proactive coding over the conventional coding technique.

Cognitive broadcast channel, where two multiantenna transmitters communicate with their respective receivers, is considered. One of the transmitters is said to be cognitive (secondary) as it is assumed to know the messages of the other (primary) transmitter non-causally. The goal is to design cooperative schemes between the two transmitters, which impose only minimal changes to the primary broadcast channel (compared to the non-cognitive scenario). Towards this end, an achievable scheme is provided under which both intra cell and inter cell interferences at the primary receivers are aligned. The interference at the secondary receivers, on the other hand, is canceled by dirty paper coding. The corresponding achievable region and an outer bound region are provided in terms of the degrees of freedom (DoF) metric. Special cases shows the optimality of the proposed scheme in the high SNR regime for those cases. We also illustrate the advantage of the cognitive cooperation over the non-cognitive system by proving that the achieved sum DoF is strictly larger than the non-cognitive case.

In a recent work, we have introduced the notion of proactive resource allocation in wireless networks whereby the predictability of user demands are leveraged to significantly enhance the spectral efficiency of the network in outage limited regimes. In this paper, we expand the horizon to the important scenario of multicast traffic. Our analysis reveals two additional types of gains that can be leveraged in this proactive multicast scenario. The first can be attributed to the basic nature of multicast traffic in which each request would represent a data source rather than a user, as it would in the unicast case. The second is the demand alignment phenomenon whereby the predictive network would wait to gather as much requests as possible and serve them altogether using the same resources. We analytically derive the impact of these advantages on the system diversity gain, which quantifies the exponential decay rate of the outage probability, and further illustrate the resulting gains via numerical results.

Downlink communication in a cellular network with a cognitive (secondary) cell is considered. In our model, the base station of the cognitive cell knows the messages of the other cell non-causally. We propose a new interference cancellation technique that zero forces the intra-cell interference in the primary cell by the help of the cognitive base station. In addition, as the primary messages are known at the cognitive base station, the interference caused by the primary base station on the secondary users are canceled using dirty paper coding (DPC). Moreover, we provide an outer bound on the achievable degrees of freedom (DoF) region and show that for some special cases the proposed signaling scheme is sum DoF optimal for the considered system when the cognitive cell operates at its maximum sum DoF. The benefit of the cognitive paradigm is also established using the derived outer-bound and showing that the achieved sum DoF is strictly larger than the case when cognitive message sharing is unavailable.

This paper develops a novel framework for sharing secret keys using the Automatic Repeat reQuest (ARQ) protocol. We first characterize the underlying information theoretic limits, under different assumptions on the channel spatial and temporal correlation function. Our analysis reveals a novel role of “dumb antennas” in overcoming the negative impact of spatial correlation on the achievable secrecy rates. We further develop an adaptive rate allocation policy, which achieves higher secrecy rates in temporally correlated channels, and explicit constructions for ARQ secrecy coding that enjoy low implementation complexity. Building on this theoretical foundation, we propose a unified framework for ARQ-based secrecy in Wi-Fi networks. By exploiting the existing ARQ mechanism in the IEEE 802.11 standard, we develop security overlays that offer strong security guarantees at the expense of only minor modifications in the medium access layer. Our numerical results establish the achievability of nonzero secrecy rates even when the eavesdropper channel is less noisy, on the average, than the legitimate channel, while our Linux-based prototype demonstrates the efficiency of our ARQ overlays in mitigating all known, passive and active, Wi-Fi attacks at the expense of a minimal increase in the link setup time and a small loss in throughput.

This paper investigates the fundamental performance limits of the two-user interference channel in the presence of an external eavesdropper. In this setting, we construct an inner bound, to the secrecy capacity region, based on the idea of cooperative encoding in which the two users cooperatively design their randomized codebooks and jointly optimize their channel prefixing distributions. Our achievability scheme also utilizes message-splitting in order to allow for partial decoding of the interference at the nonintended receiver. Outer bounds are then derived and used to establish the optimality of the proposed scheme in certain cases. In the Gaussian case, the previously proposed cooperative jamming and noise-forwarding techniques are shown to be special cases of our proposed approach. Overall, our results provide structural insights on how the interference can be exploited to increase the secrecy capacity of wireless networks.

This paper studies the frequency/time selectiveK-user Gaussian interference channel with secrecy constraints. Two distinct models, namely the interference channel with confidential messages and the interference channel with an external eavesdropper, are analyzed. The key difference between the two models is the lack of channel state information (CSI) of the external eavesdropper. Using interference alignment along with secrecy precoding, it is shown that each user can achieve non-zero secure degrees of freedom (DoF) for both cases. More precisely, the proposed coding scheme achieves [(K-2)/(2K-2)] secure DoF with probability one per user in the confidential messages model. For the external eavesdropper scenario, on the other hand, it is shown that each user can achieve [(K-2)/(2K)] secure DoF in the ergodic setting. Remarkably, these results establish the positive impact of interference on the secrecy capacity region of wireless networks.

This paper considers the design of efficient strategies that allow cognitive users to choose frequency bands to sense and access among multiple bands with unknown parameters. First, the scenario in which a single cognitive user wishes to opportunistically exploit the availability of frequency bands is considered. By adopting tools from the classical bandit problem, optimal as well as low complexity asymptotically optimal solutions are developed. Next, the multiple cognitive user scenario is considered. The situation in which the availability probability of each channel is known is first considered. An optimal symmetric strategy that maximizes the total throughput of the cognitive users is developed. To avoid the possible selfish behavior of the cognitive users, a game-theoretic model is then developed. The performance of both models is characterized analytically. Then, the situation in which the availability probability of each channel is unknown a priori is considered. Low-complexity medium access protocols, which strike an optimal balance between exploration and exploitation in such competitive environments, are developed. The operating points of these low-complexity protocols are shown to converge to those of the scenario in which the availability probabilities are known. Finally, numerical results are provided to illustrate the impact of sensing errors and other practical considerations.

In recent years, the famous wiretap channel has been revisited by many researchers and information theoretic secrecy has become an active area of research in this setting. In this paper, we design a wireless communication system that achieves constant bit rate data transmission over a block fading channel, securely from an eavesdropper that listens to the transmitter over another independent block fading channel. It is well known that, the method of sending secure information using the binning techniques inspired by the wiretap channel fails to secure the information at times when the eavesdropper channel has favorable conditions over the main channel. This phenomenon is called secrecy outage. In our system, however, we exploit the times at which the main channel is favorable over the eavesdropper channel for us to be able to transmit some random secret key bits along with the data bits. These key bits are stored in a separate key queue at the transmitter as well as the receiver, and are utilized to secure data bits, whenever the channel conditions favor the eavesdropper. We show that, our system achieves a high performance at any given desired outage probability by jointly controlling the key queue and the transmit power. We show that the optimal power control involves a time sharing between secure waterfilling and channel inversion strategies and the key queue operates in the heavy traffic regime to achieve the maximum delay limited rate possible, under a small outage constraint. This work can be viewed as a first step in providing a framework that combines both information theory and queueing analysis for the study of information theoretic security.

A secure communication game is considered for the cognitive channel with a confidential primary message, where the primary user is interested in maximizing its secure rate with lowest possible power consumption and the utility of the cognitive user is a weighted sum of the primary secrecy rate and the cognitive rate (corresponds to a spectrum law in favor of the legacy owners of the spectrum). An achievable rate region is derived for the channel with message splitting at the cognitive radio and noise forwarding. The game considers the case with no common message, but shows that even this limited scenario can still be beneficial. The established Nash Equilibrium (NE) shows that the cognitive user trades noise for bits. The results are also interesting in the sense that both users can benefit (by playing the distributed game) compared to their throughput resulting from the non-cooperative scenario.

In this paper, we completely characterize the deterministic multicast capacity region of the symmetric two-pair bidirectional half duplex relay network with private messages. Towards this end, we first develop a new upper bound on the deterministic capacity region, based on the notion of a one-sided genie. We then proceed to construct novel detour schemes that achieve the upper bound by routing the bits intended for a certain receiver through the network rather than sending it directly. To the best of the authors' knowledge, this scenario corresponds to one of the rare cases where coding, across levels and time, is needed to achieve the deterministic capacity of the network.

Wyner's work on wiretap channels and the recent works on information theoretic security are based on random codes. Achieving information theoretical security with practical coding schemes is of definite interest. In this note, the attempt is to overcome this elusive task by employing the polar coding technique of Arikan. It is shown that polar codes achieve nontrivial perfect secrecy rates for binary-input degraded wiretap channels while enjoying their low encoding-decoding complexity. In the special case of symmetric main and eavesdropper channels, this coding technique achieves the secrecy capacity. Next, fading erasure wiretap channels are considered and a secret key agreement scheme is proposed, which requires only the statistical knowledge of the eavesdropper channel state information (CSI). The enabling factor is the creation of advantage over Eve, by blindly using the proposed scheme over each fading block, which is then exploited with privacy amplification techniques to generate secret keys.

This paper develops a new physical layer framework for secure two-way wireless communication in the presence of a passive eavesdropper, i.e., Eve. Our approach achieves perfect information theoretic secrecy via a novel randomized scheduling and power allocation scheme. The key idea is to allow Alice and Bob to send symbols at random time instants. While Alice will be able to determine the symbols transmitted by Bob, Eve will suffer from ambiguity regarding the source of any particular symbol. This desirable ambiguity is enhanced, in our approach, by randomizing the transmit power level. Our theoretical analysis, in a 2-D geometry, reveals the ability of the proposed approach to achieve relatively high secure data rates under mild conditions on the spatial location of Eve. These theoretical claims are then validated by experimental results using IEEE 802.15.4-enabled sensor boards in different configurations, motivated by the spatial characteristics of Wireless Body Area Networks (WBAN).

This paper develops a novel framework for sharing secret keys using existing automatic repeat request (ARQ) protocols. Our approach exploits the multi-path nature of the wireless environment to hide the key from passive eavesdroppers. The proposed framework does not assume the availability of any prior channel state information (CSI) and exploits only the one bit ACK/NACK feedback from the legitimate receiver. Compared with earlier approaches, the main innovation lies in the distribution of key bits among multiple ARQ frames. Interestingly, this idea allows for achieving a positive secrecy rate even when the eavesdropper experiences more favorable channel conditions, on average, than the legitimate receiver. In the sequel, we characterize the information theoretic limits of the proposed schemes, develop low complexity explicit implementations, and conclude with numerical results that validate our theoretical claims.

We consider the design of cognitive medium access control (MAC) protocols enabling an unlicensed (secondary) transmitter-receiver pair to communicate over the idle periods of a set of licensed channels, i.e., the primary network. The objective is to maximize data throughput while maintaining the synchronization between secondary users and avoiding interference with licensed (primary) users. No statistical information about the primary traffic is assumed to be available a-priori to the secondary user. We investigate two distinct sensing scenarios. In the first, the secondary transmitter is capable of sensing all the primary channels, whereas it senses one channel only in the second scenario. In both cases, we propose MAC protocols that efficiently learn the statistics of the primary traffic online. Our simulation results demonstrate that the proposed blind protocols asymptotically achieve the throughput obtained when prior knowledge of primary traffic statistics is available.

In this paper, the delay limited secrecy capacity of the flat fading channel is investigated under two different assumptions on the available transmitter channel state information (CSI). The first scenario assumes perfect prior knowledge of both the main and eavesdropper channel gains. Here, upper and lower bounds on the secure delay limited capacity are derived and shown to be tight in the high signal-to-noise ratio (SNR) regime (for a wide class of channel distributions). In the second scenario, only the main channel CSI is assumed to be available at the transmitter. Remarkably, under this assumption, we establish the achievability of non-zero secure rate (for a wide class of channel distributions) under a strict delay constraint. In the two cases, our achievability arguments are based on a novel two-stage approach that overcomes the secrecy outage phenomenon observed in earlier works.

We consider the discrete memoryless X channel, a communication model with two transmitters and two receivers in which every transmitter has a message for every receiver. We propose an achievable scheme, based on the message splitting and binning techniques, which results in the best inner bound on the capacity region of the X channel to date.

This paper considers an interference network composed of K half-duplex single-antenna pairs of users who wish to establish bi-directional communication with the aid of a multi-input-multi-output (MIMO) half-duplex relay node. This channel is referred to as the ¿MIMO wireless switch¿ since, for the sake of simplicity, our model assumes no direct link between the two end nodes of each pair implying that all communication must go through the relay node (i.e., the MIMO switch). Assuming a delay-limited scenario, the fundamental limits in the high signal-to-noise ratio (SNR) regime is analyzed using the diversity-multiplexing tradeoff (DMT) framework. Our results sheds light on the structure of optimal transmission schemes and the gain offered by the relay node in two distinct cases, namely reciprocal and non-reciprocal channels (between the relay and end-users). In particular, the existence of a relay node, equipped with a sufficient number of antennas, is shown to increase the multiplexing gain; as compared with the traditional fully connected K-pair interference channel. To the best of our knowledge, this is the first known example where adding a relay node results in enlarging the pre-log factor of the sum rate. Moreover, for the case of reciprocal channels, it is shown that, when the relay has a number of antennas at least equal to the sum of antennas of all the users, static time allocation of decode and forward (DF) type schemes is optimal. On the other hand, in the non-reciprocal scenario, we establish the optimality of dynamic decode and forward in certain relevant scenarios.

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.

An authentication counterpart of Wyner's study of the wiretap channel is developed in this work. More specifically, message authentication over noisy channels is studied while impersonation and substitution attacks are investigated for both single- and multiple-message scenarios. For each scenario, information-theoretic lower and upper bounds on the opponent's success, or cheating, probability are derived. Remarkably, in both scenarios, the lower and upper bounds are shown to match, and hence, the fundamental limits on message authentication over noisy channels are fully characterized. The opponent's success probability is further shown to be smaller than that derived in the classical noiseless channel model. These results rely on a novel authentication scheme in which shared key information is used to provide simultaneous protection against both types of attacks. Finally, message authentication for the case in which the source and receiver possess only correlated sequences is studied.

This paper considers the generalized cognitive radio channel where the secondary user is allowed to reuse the frequency during both the idle and active periods of the primary user, as long as the primary rate remains the same. In this setting, the optimal power allocation policy with single-input single-output (SISO) primary and secondary channels is explored. Interestingly, the offered gain resulting from the frequency reuse during the active periods of the spectrum is shown to disappear in both the low and high signal-to-noise ratio (SNR) regimes. We then argue that this drawback in the high SNR region can be avoided by equipping both the primary and secondary transmitters with multiple antennas. Finally, the scenario consisting of SISO primary and multi-input multi-output (MIMO) secondary channels is investigated. Here, a simple zero-forcing approach is shown to significantly outperform the celebrated decoding- forwarding-dirty paper coding strategy (especially in the high SNR regime).

The design of medium access control protocols for a cognitive user wishing to opportunistically exploit frequency bands within parts of the radio spectrum having multiple bands is considered. In the scenario under consideration, the availability probability of each channel is unknown a priori to the cognitive user. Hence efficient medium access strategies must strike a balance between exploring the availability of channels and exploiting the opportunities identified thus far. Using a sequential design approach, an optimal medium access strategy is derived. To avoid the prohibitive computational complexity of this optimal strategy, a low complexity asymptotically optimal strategy is also developed. The proposed strategy does not require any prior statistical knowledge about the traffic pattern on the different channels.

This paper studies the K-user Gaussian interference channel with secrecy constraints. Two distinct network models, namely the interference channel with confidential messages and the one with an external eavesdropper, are analyzed. Using interference alignment along with secrecy pre-coding at each transmitter, it is shown that each user in the network can achieve non-zero secure Degrees of Freedoms (DoFs) in both scenarios. In particular, the proposed coding scheme achieves K−2/2K−2 secure DoFs for each user in the interference channel with confidential messages model, and K−2/2K secure DoFs in the case of an external eavesdropper. The fundamental difference between the two scenarios stems from the lack of channel state information (CSI) about the external eavesdropper. Remarkably, the results establish the positive impact of interference on the secrecy capacity of wireless networks.

This paper studies interference channels with security constraints. The existence of an external eavesdropper in a two-user interference channel is assumed, where the network users would like to secure their messages from the external eavesdropper. The cooperative binning and channel prefixing scheme is proposed for this system model which allows users to cooperatively add randomness to the channel in order to degrade the observations of the external eavesdropper. This scheme allows users to add randomness to the channel in two ways: 1) Users cooperate in their design of the binning codebooks, and 2) Users cooperatively exploit the channel prefixing technique. As an example, the channel prefixing technique is exploited in the Gaussian case to transmit a superposition signal consisting of binning codewords and independently generated noise samples. Gains obtained form the cooperative binning and channel prefixing scheme compared to the single user scenario reveals the positive effect of interference in increasing the network security. Remarkably, interference can be exploited to cooperatively add randomness into the network in order to enhance the security.

In this correspondence, the performance of the automatic repeat request-dynamic decode and forward (ARQ-DDF) cooperation protocol is analyzed in two distinct scenarios. The first scenario is the multiple access relay channel where a single relay is dedicated to simultaneously help two multiple access users. For this setup, it is shown that the ARQ-DDF protocol achieves the channel's optimal diversity multiplexing tradeoff (DMT). The second scenario is the cooperative vector multiple access channel where two users cooperate in delivering their messages to a destination equipped with two receiving antennas. For this setup, a new variant of the ARQ-DDF protocol is developed where the two users are purposefully instructed not to cooperate in the first round of transmission. Lower and upper bounds on the achievable DMT are then derived. These bounds are shown to converge to the optimal tradeoff as the number of transmission rounds increases.

In this correspondence, we derive a simplified description of the Han–Kobayashi rate region for the general interference channel. Using this result, we establish that the recently discovered Chong–Motani–Garg rate region is a new representation of the Han–Kobayashi region. Moreover, a tighter bound for the cardinality of the time-sharing auxiliary random variable emerges from our simplified description.

We consider the secure transmission of information over an ergodic fading channel in the presence of an eavesdropper. Our eavesdropper can be viewed as the wireless counterpart of Wyner's wiretapper. The secrecy capacity of such a system is characterized under the assumption of asymptotically long coherence intervals. We first consider the full channel state information (CSI) case, where the transmitter has access to the channel gains of the legitimate receiver and the eavesdropper. The secrecy capacity under this full CSI assumption serves as an upper bound for the secrecy capacity when only the CSI of the legitimate receiver is known at the transmitter, which is characterized next. In each scenario, the perfect secrecy capacity is obtained along with the optimal power and rate allocation strategies. We then propose a low-complexity on/off power allocation strategy that achieves near-optimal performance with only the main channel CSI. More specifically, this scheme is shown to be asymptotically optimal as the average signal-to-noise ratio (SNR) goes to infinity, and interestingly, is shown to attain the secrecy capacity under the full CSI assumption. Overall, channel fading has a positive impact on the secrecy capacity and rate adaptation, based on the main channel CSI, is critical in facilitating secure communications over slow fading channels.

A game-theoretic framework is developed to design and analyze the resource allocation algorithms in fading multiple-access channels (MACs), where the users are assumed to be selfish, rational, and limited by average power constraints. The maximum sum-rate point on the boundary of the MAC capacity region is shown to be the unique Nash equilibrium of the corresponding water-filling game. This result sheds a new light on the opportunistic communication principle. The base station is then introduced as a player interested in maximizing a weighted sum of the individual rates. A Stackelberg formulation is proposed in which the base station is the designated game leader. In this setup, the base station announces first its strategy defined as the decoding order of the different users, in the successive cancellation receiver, as a function of the channel state. In the second stage, the users compete conditioned on this particular decoding strategy. This formulation is shown to be able to achieve all the corner points of the capacity region, in addition to the maximum sum-rate point. On the negative side, it is shown that there does not exist a base station strategy in this formulation that achieves the rest of the boundary points. To overcome this limitation, a repeated game approach, which achieves the capacity region of the fading MAC, is presented. Finally, the study is extended to vector channels highlighting interesting differences between this scenario and the scalar channel case.

This paper establishes the utility of user cooperation in facilitating secure wireless communications. In particular, the four-terminal relay–eavesdropper channel is introduced and an outer-bound on the optimal rate-equivocation region is derived. Several cooperation strategies are then devised and the corresponding achievable rate-equivocation region are characterized. Of particular interest is the novel noise-forwarding (NF) strategy, where the relay node sends codewords independent of the source message to confuse the eavesdropper. This strategy is used to illustrate the deaf helper phenomenon, where the relay is able to facilitate secure communications while being totally ignorant of the transmitted messages. Furthermore, NF is shown to increase the secrecy capacity in the reversely degraded scenario, where the relay node fails to offer performance gains in the classical setting. The gain offered by the proposed cooperation strategies is then proved theoretically and validated numerically in the additive white Gaussian noise (AWGN) channel.

In this work, the critical role of noisy feedback in enhancing the secrecy capacity of the wiretap channel is established. Unlike previous works, where a noiseless public discussion channel is used for feedback, the feed-forward and feedback signals share the same noisy channel in the present model. Quite interestingly, this noisy feedback model is shown to be more advantageous in the current setting. More specifically, the discrete memoryless modulo-additive channel with a full-duplex destination node is considered first, and it is shown that the judicious use of feedback increases the secrecy capacity to the capacity of the source-destination channel in the absence of the wiretapper. In the achievability scheme, the feedback signal corresponds to a private key, known only to the destination. In the half-duplex scheme, a novel feedback technique that always achieves a positive perfect secrecy rate (even when the source-wiretapper channel is less noisy than the source-destination channel) is proposed. These results hinge on the modulo-additive property of the channel, which is exploited by the destination to perform encryption over the channel without revealing its key to the source. Finally, this scheme is extended to the continuous real valued modulo-Lambda channel where it is shown that the secrecy capacity with feedback is also equal to the capacity in the absence of the wiretapper.

In wireless networks with energy limited nodes, user cooperation is usually exploited to reduce the network energy consumption. In many practical scenarios, however, nodes' selfishness raises doubts on whether each node will be willing to spend its valuable energy in forwarding packets for other users. To analyze this problem, a non-cooperative game theoretic framework is adopted in our work. Using this framework, the critical role of altruistic nodes in encouraging cooperation is established, both for small and large scale networks. In a small network, where nodes utilize the Decode-Forward scheme to cooperate, we show that a relay node, with appropriate strategy and location, successfully turns the Nash Equilibrium from no- cooperation to full-cooperation. In the large scale network, we show that it is sufficient to have a vanishingly small fraction of the nodes to be altruistic, i.e., relay nodes, in order to ensure full cooperation from all the nodes in the network. This result hinges on using the appropriate forwarding policies by the altruistic nodes, as detailed in the sequel. Our work also establishes the sub-optimality of traditional relaying strategies, which ignore the game-theoretic aspect of the problem. An important aspect of our work is that only reward/punishment policies that can be realized on the physical layer are used, and hence, our results establish the achievability of full cooperation without requiring additional incentive mechanisms at the application layer.

It is well known that a non-zero secrecy capacity of the wiretap channel is only possible when the legitimate receiver is less noisy than the wiretapper. This work shows that user cooperation is an efficient solution to this limitation. In particular, the four-terminal wiretap relay channel is considered in our work where several cooperation strategies, that enable secure communication, are constructed and the corresponding rate-equivocation regions are characterized. Of particular interest is the novel noise forwarding strategy which establishes the deaf helper phenomenon. Here, the relay is able to facilitate secure communication over the main channel while being totally ignorant of the transmitted message. The gain offered by the proposed strategies is proved theoretically and validated numerically in the additive white Gaussian noise (AWGN) channel. Overall, our work establishes the utility of user cooperation in facilitating secure communication over wireless channels.

This paper considers wireless networks with energy limited nodes. In this scenario, multi-hop forwarding is needed to minimize the network energy consumption. In many practical scenarios, however, nodes' selfishness raises doubts on whether each node will be willing to forward packets in order to minimize the overall energy expenditure. To analyze this problem, a non-cooperative game theoretic approach is adopted in our work. Using this framework, the critical role of altruistic nodes in encouraging cooperation is established. More specifically, we show that it is sufficient to have a vanishingly small fraction of the nodes to be altruistic, i.e., relay nodes, in order to ensure full cooperation from all the nodes in the network. This result hinges on using the appropriate forwarding policies by the altruistic nodes, as detailed in the sequel. An important aspect of our work is that only reward/punishment policies that can be realized on the physical layer are used, and hence, our results establish the achievability of full cooperation without requiring additional incentive mechanisms at the higher layer.

A cross-layer approach is adopted for the design of finite-user symmetric random access wireless systems. Instead of the traditional collision model, a more realistic physical layer model is adopted. An incremental redundancy automatic repeat request (IR-ARQ) scheme, tailored to jointly combat the effects of user collisions, multi-path fading, and channel noise, is proposed. The diversity-multiplexing-delay tradeoff of the proposed scheme is analyzed for fully-loaded queues, and compared with that of the Gallager tree algorithm for collision resolution and the network-assisted diversity multiple access (NDMA) protocol of Tsatsanis et at.. The fully-loaded queue model is then replaced by one with random arrivals, where the three protocols are compared in terms of the stability region and average delay. Overall, our analytical and numerical results establish the superiority of the proposed IR-ARQ scheme and reveal some important insights. For example, it turns out that the performance is optimized, for a given total throughput, by maximizing the probability that a certain user will send a new packet and minimizing the transmission rate employed by each user.

In the evolutionary biology literature, canalization refers to the mechanism by which variability is reduced at the phenotypical level. It was first observed by Waddington in 1942 and has been the focus of recent research interest. Here, we attempt to build a bridge between evolutionary biology and information theory by offering a fresh coding theoretic perspective of canalization. In particular, we focus on evolution in rugged multi-peak fitness landscapes and argue that canalization can efficiently smooth-out the roughness of the landscape, and hence, facilitate easier transitions from lower to higher peaks. Inspired by coding theory, we view the landscape peaks as codewords and allow our population to learn the underlying codebook and decision regions through evolution. Interestingly, our model sheds more light on the interplay between robustness, neutrality, and evolvability. Finally, we support our claims by numerical results generated through Monte-Carlo simulations in polynomial fitness landscapes.

We consider the secure transmission of information over an ergodic fading channel in the presence of an eavesdropper. Our eavesdropper can be viewed as the wireless counterpart of Wyner's wiretapper. The secrecy capacity of such a system is characterized under the assumption of asymptotically long coherence intervals. We analyze the full Channel State Information (CSI) case, where the transmitter has access to the channel gains of the legitimate receiver and eavesdropper, and the main channel CSI scenario, where only the legitimate receiver channel gain is known at the transmitter. In each scenario, the secrecy capacity is obtained along with the optimal power and rate allocation strategies. We then propose a low-complexity on/off power allocation strategy that achieves near-optimal performance with only the main channel CSI. More specifically, this scheme is shown to be asymptotically optimal as the average SNR goes to infinity, and interestingly, is shown to attain the secrecy capacity under the full CSI assumption. Remarkably, our results reveal the positive impact of fading on the secrecy capacity and establish the critical role of rate adaptation, based on the main channel CSI, in facilitating secure communications over slow fading channels.

We consider the generalized cognitive radio channel where the secondary user is allowed to reuse the frequency during the active periods of the primary user, as long as the primary rate remains the same. In this setting, the optimal power allocation policy with a single antenna secondary transmitter (and receiver) is explored. Interestingly, we show that the offered gain resulting from the frequency reuse during the active periods of the spectrum disappears in both the low and high signal-to- noise ratio (SNR) regimes. This drawback, however, is shown to disappear with multi-antenna nodes by using simple zero-forcing strategies at both ends of the secondary channel.

This paper investigates the role of user cooperation in facilitating secure wireless communications. In particular, the four-terminal relay-eavesdropper channel is introduced and analyzed. Several cooperation strategies are devised and the corresponding achievable rate-equivocation region are characterized. Of particular interest is the novel Noise-Forwarding (NF) strategy, where the relay node sends codewords independent of the source message to confuse the eavesdropper. This strategy is used to illustrate the deaf helper phenomenon, where the relay is able to facilitate secure communications while being totally ignorant of the transmitted messages. Furthermore, NF is shown to increase the perfect secrecy rate in the reversely degraded scenario, where the relay node fails to offer performance gains in the classical setting. The gain offered by the proposed cooperation strategies is then proved theoretically and validated numerically in the additive white Gaussian noise (AWGN) channel.

In this paper, we consider a class of multiple access lattice space-time coding and decoding schemes. We prove an extended version of the Minkowski-Hlawka theorem, utilizing independent Loeliger ensembles. Applying this extension, we prove that lattice coding and decoding achieves the optimal diversity-multiplexing tradeoff of multiple access channels.

Summary form only given. In this talk, we report some of the recent results on non traditional relay channels. More specifically, the outage-limited relay channel is discussed first. Here, a simple implementation of the dynamic decode and forward relaying scheme is presented. This scheme achieved the optimal diversity-multiplexing tradeoff for multiplexing gains r les 0.5. In the second part of the talk, we impose a secrecy constraint on the relay channel by introducing an eavesdropper to the basic setup. Several cooperation strategies for enhancing the secrecy capacity are devised, and the corresponding achievable rate-equivocation region is characterized. Of particular interest is the novel noise-forwarding (NF) strategy, where the relay node sends codewords independent of the source message to confuse the eavesdropper. This strategy is used to illustrate the deaf helper phenomenon, where the relay is able to facilitate secure communications while being totally ignorant of the transmitted messages. Furthermore, NF is shown to increase the secrecy capacity in the reversely degraded scenario, where the relay node fails to offer performance gains in the classical setting.

We propose novel lattice coding/decoding schemes for half-duplex outage-limited cooperative channels. These schemes are inspired by the cooperation protocols of Azarian et al. and enjoy an excellent performance-complexity tradeoff. More specifically, for the. relay channel, we first use our lattice coding framework to generalize Yang and Belfiore implementation of the non-orthogonal amplify and forward cooperation protocol. This generalization is shown to offer significant performance gains while keeping the decoding complexity manageable. We then devise a novel variant of the dynamic decode and forward protocol, along with a lattice-coded implementation, which enjoys a near-optimal diversity-multiplexing tradeoff with a low encoding/decoding complexity. Finally, for the cooperative multiple-access channel, we present a lattice-coded implementation of the non-orthogonal amplify and forward protocol and demonstrate its excellent performance-complexity tradeoff. Throughout the paper, we establish the performance gains of our proposed protocols via a comprehensive simulation study.

We build on Zheng and Tse's elegant formulation of diversity-multiplexing tradeoff (DMT) to provide a better understanding of the asymptotic interplay between transmission rate, error probability, and signal-to-noise ratio (SNR) in block-fading multiple-input multiple-output (MIMO) channels. In particular, we identify the limitation imposed by the notion of multiplexing gain and develop a new formulation called the throughput-reliability tradeoff (TRT), that avoids this limitation. The new characterization is then used to elucidate the asymptotic trends exhibited by the outage probability curves of block-fading MIMO channels.

In this correspondence, we consider communication over automatic repeat request (ARQ) memoryless channels with deadlines. In particular, an upper bound L is imposed on the maximum number of ARQ transmission rounds. In this setup, it is shown that incremental redundancy ARQ outperforms Forney's memoryless decoding in terms of the achievable error exponents.

The thirty-four papers in this special issue are devoted to models, theories, and codes for relaying and cooperation in communication networks. The demand for large, more efficient, reliable, and cost effective communication networks is motivating new network architectures for cellular and wireless communications as well as cognitive radio and sensor networks.

In this paper, an outage limited MIMO channel is considered. We build on Zheng and Tse's elegant formulation of diversity-multiplexing tradeoff to develop a better understanding of the asymptotic relationship between probability of error, transmission rate and signal-to-noise ratio. We identify the limitation imposed by the notion of multiplexing gain and develop a new formulation for the throughput-reliability tradeoff that avoids this limitation. The new characterization is then used to shed more light on the asymptotic trends exhibited by the outage probability curves of MIMO channels

We adopt a game theoretic approach for the design and analysis of distributed resource allocation algorithms in fading multiple access channels, where the users are assumed to be selfish, rational and limited by average power constraints. We show that the sum-rate optimal point on the boundary of the multiple access channel capacity region is the unique Nash equilibrium of the corresponding water-filling game. The base-station is then introduced as a player interested in maximizing a weighted sum of the individual rates. We propose a Stackelberg formulation in which the base-station is the designated game leader. We show that this formulation allows for achieving all the corner points of the capacity region, in addition to the sum-rate optimal point. On the negative side, we prove the non-existence of a base-station strategy in this formulation that achieves the rest of the boundary points. To overcome this limitation, we present a repeated game approach which achieves the capacity region of the fading multiple access channel. Finally, we extend our study to vector channels highlighting interesting differences between this scenario and the scalar channel case

A simple and general form of threaded algebraic space–time (TAST) codes and constellations for arbitrary numbers of transmit and receive antennas and arbitrary input alphabets is given and analyzed. This new form gives revealing insights on the TAST framework, elucidates the connection between space–time constellation expansion and the peak-to-average power ratio (PAR), and establishes the equivalence between a certain class of TAST constellations and constellations derived from division algebras.

In this paper, the fundamental performance tradeoff of the delay-limited multiple-input multiple-output (MIMO) automatic retransmission request (ARQ) channel is explored. In particular, we extend the diversity-multiplexing tradeoff investigated by Zheng and Tse in standard delay-limited MIMO channels with coherent detection to the ARQ scenario. We establish the three-dimensional tradeoff between reliability (i.e., diversity), throughput (i.e., multiplexing gain), and delay (i.e., maximum number of retransmissions). This tradeoff quantifies the ARQ diversity gain obtained by leveraging the retransmission delay to enhance the reliability for a given multiplexing gain. Interestingly, ARQ diversity appears even in long-term static channels where all the retransmissions take place in the same channel state. Furthermore, by relaxing the input power constraint allowing variable power levels in different retransmissions, we show that power control can be used to dramatically increase the diversity advantage. Our analysis reveals some important insights on the benefits of ARQ in slow-fading MIMO channels. In particular, we show that 1) allowing for a sufficiently large retransmission delay results in an almost flat diversity-multiplexing tradeoff, and hence, renders operating at high multiplexing gain more advantageous; 2) MIMO ARQ channels quickly approach the ergodic limit when power control is employed. Finally, we complement our information-theoretic analysis with an incremental redundancy lattice space-time (IR-LAST) coding scheme which is shown, through a random coding argument, to achieve the optimal tradeoff(s). An integral component of the optimal IR-LAST coding scheme is a list decoder, based on the minimum mean-square error (MMSE) lattice decoding principle, for joint error detection and correction. Throughout the paper, our theoretical claims are validated by numerical results

We consider a wireless network composed of three nodes and limited by the half-duplex and total power constraints. This formulation encompasses many of the special cases studied in the literature and allows for capturing the common features shared by them. Here, we focus on three special cases, namely, 1) relay channel, 2) multicast channel, and 3) three-way channel. These special cases are judicially chosen to reflect varying degrees of complexity while highlighting the common ground shared by the different variants of the three-node wireless network. For the relay channel, we propose a new cooperation scheme that exploits the wireless feedback gain. This scheme combines the benefits of the decode-and-forward (DF) and compress-and-forward (CF) strategies and avoids the noiseless feedback assumption adopted in earlier works. Our analysis of the achievable rate of this scheme reveals the diminishing feedback gain in both the low and high signal-to-noise ratio (SNR) regimes. Inspired by the proposed feedback strategy, we identify a greedy cooperation framework applicable to both the multicast and three-way channels. Our performance analysis reveals the asymptotic optimality of the proposed greedy approach and the central role of list source-channel decoding in exploiting the receiver side information in the wireless network setting.

We consider receiver design for coded transmission over linear Gaussian channels. We restrict ourselves to the class of lattice codes and formulate the joint detection and decoding problem as a closest lattice point search (CLPS). Here, a tree search framework for solving the CLPS is adopted. In our framework, the CLPS algorithm is decomposed into the preprocessing and tree search stages. The role of the preprocessing stage is to expose the tree structure in a form matched to the search stage. We argue that the forward and feedback (matrix) filters of the minimum mean-square error decision feedback equalizer (MMSE-DFE) are instrumental for solving the joint detection and decoding problem in a single search stage. It is further shown that MMSE-DFE filtering allows for solving underdetermined linear systems and using lattice reduction methods to diminish complexity, at the expense of a marginal performance loss. For the search stage, we present a generic method, based on the branch and bound (BB) algorithm, and show that it encompasses all existing sphere decoders as special cases. The proposed generic algorithm further allows for an interesting classification of tree search decoders, sheds more light on the structural properties of all known sphere decoders, and inspires the design of more efficient decoders. In particular, an efficient decoding algorithm that resembles the well-known Fano sequential decoder is identified. The excellent performance-complexity tradeoff achieved by the proposed MMSE-DFE Fano decoder is established via simulation results and analytical arguments in several multiple-input multiple-output (MIMO) and intersymbol interference (ISI) scenarios.

In this paper, we consider both the down-link and up-link of a cellular communication system operated under strict delay constraints. We further assume that, except for the one-bit ACK/NACK signal associated with the automatic retransmission request (ARQ) protocol, no channel state information (CSI) is available at the transmitter(s). In this setting, we establish the critical role of multi-user diversity in facilitating ARQ gain, while satisfying an upper-bound on the maximum overall delay (i.e., queuing plus transmission). In order to distinguish between the different types of gains offered by multi-user diversity, we first derive our results for a symmetric multi-user channel where we consider the down-link (broadcast) and up-link (multiple-access) scenarios separately. This reveals the interaction between multi-user diversity and ARQ gain. Then, we extend our study to the multi-user relay channel where a number of half-duplex relays are devoted to facilitate the communication. The analysis of this scenario highlights the role of multiuser diversity in allowing a large number of users to significantly benefit from a few dedicated relays

In this paper, we explore the fundamental performance tradeoff of the delay-limited multi-input-multi-output (MIMO) automatic retransmission request (ARQ) channel. In particular, we extend the diversity-multiplexing tradeoff investigated by Zheng and Tse in standard delay-limited MIMO channels with coherent detection to the ARQ scenario. We establish the three-dimensional tradeoff between reliability (i.e. diversity), throughput (i.e., multiplexing gain), and delay (i.e., maximum number of retransmissions). This tradeoff quantifies the ARQ diversity gain obtained by leveraging the retransmission delay to enhance the reliability for a given multiplexing gain. Interestingly, ARQ diversity appears even in long-term static channels where all the retransmissions take place in the same channel state. Furthermore, by relaxing the input power constraint allowing variable power levels in different retransmissions, we show that power control can be used to dramatically increase the diversity advantage. Our analysis reveals some important insights on the benefits of ARQ in slow fading MIMO channels. In particular, we show that: 1) allowing for a sufficiently large retransmission delay results in an almost flat diversity-multiplexing tradeoff, and hence, renders operating at high multiplexing gain more advantageous; 2) MIMO ARQ channels quickly approach the ergodic limit when power control is employed

We consider receiver design for coded transmission over linear Gaussian channels. We restrict ourselves to the class of lattice codes and formulate the joint detection and decoding problem as a closest lattice point search (CLPS). Here, a tree search framework for solving the CLPS is adopted. In our framework, the CLPS algorithm decomposes into preprocessing and tree search stages. The role of the preprocessing stage is to expose the tree structure in a form matched to the search stage. Here, it is argued that the minimum mean square error decision feedback (MMSE-DFE) frontend is instrumental for solving the joint detection and decoding problem in a single search stage. It is further shown that MMSE-DFE filtering allows for using lattice reduction methods to reduce complexity, at the expense of a marginal performance loss, and solving under-determined linear systems. For the search stage, we present a generic method, based on the branch and bound (BB) algorithm, and show that it encompasses all existing sphere decoders as special cases. The proposed generic algorithm further allows for an interesting classification of tree search decoders, sheds more light on the structural properties of all known sphere decoders, and inspires the design of more efficient decoders. In particular, an efficient decoding algorithm that resembles the well known Fano sequential decoder is identified. The excellent performance-complexity tradeoff achieved by the proposed MMSE-Fano decoder is established via simulation results and analytical arguments in several MIMO and ISI scenarios.

We propose novel cooperative transmission protocols for delay-limited coherent fading channels consisting of N (half-duplex and single-antenna) partners and one cell site. In our work, we differentiate between the relay, cooperative broadcast (down-link), and cooperative multiple-access (CMA) (up-link) channels. The proposed protocols are evaluated using Zheng-Tse diversity-multiplexing tradeoff. For the relay channel, we investigate two classes of cooperation schemes; namely, amplify and forward (AF) protocols and decode and forward (DF) protocols. For the first class, we establish an upper bound on the achievable diversity-multiplexing tradeoff with a single relay. We then construct a new AF protocol that achieves this upper bound. The proposed algorithm is then extended to the general case with (N-1) relays where it is shown to outperform the space-time coded protocol of Laneman and Wornell without requiring decoding/encoding at the relays. For the class of DF protocols, we develop a dynamic decode and forward (DDF) protocol that achieves the optimal tradeoff for multiplexing gains 0lesrles1/N. Furthermore, with a single relay, the DDF protocol is shown to dominate the class of AF protocols for all multiplexing gains. The superiority of the DDF protocol is shown to be more significant in the cooperative broadcast channel. The situation is reversed in the CMA channel where we propose a new AF protocol that achieves the optimal tradeoff for all multiplexing gains. A distinguishing feature of the proposed protocols in the three scenarios is that they do not rely on orthogonal subspaces, allowing for a more efficient use of resources. In fact, using our results one can argue that the suboptimality of previously proposed protocols stems from their use of orthogonal subspaces rather than the half-duplex constraint.

We consider dense wireless sensor networks deployed to observe arbitrary random fields. The requirement is to reconstruct an estimate of the random field at a certain collector node. This creates a many-to-one data gathering wireless channel. In this note, we first characterize the transport capacity of many-to-one dense wireless networks subject to a constraint on the total average power. In particular, we show that the transport capacity scales as /spl Theta/(log(N)) when the number of sensors N grows to infinity and the total average power remains fixed. We then use this result along with some information-theoretic tools to derive sufficient and necessary conditions that characterize the set of observable random fields by dense sensor networks. In particular, for random fields that can be modeled as discrete random sequences, we derive a certain form of source/channel coding separation theorem. We further show that one can achieve any desired nonzero mean-square estimation error for continuous, Gaussian, and spatially bandlimited fields through a scheme composed of single-dimensional quantization, distributed Slepian-Wolf source coding, and the proposed antenna sharing strategy. Based on our results, we revisit earlier conclusions about the feasibility of data gathering applications using dense sensor networks.

The design of space-time signals for noncoherent block-fading channels where the channel state information is not known a priori at the transmitter and the receiver is considered. In particular, a new algebraic formulation for the diversity advantage design criterion is developed. The new criterion encompasses, as a special case, the well-known diversity advantage for unitary space-time signals and, more importantly, applies to arbitrary signaling schemes and arbitrary channel distributions. This criterion is used to establish the optimal diversity-versus-rate tradeoff for training based schemes in block-fading channels. Our results are then specialized to the class of affine space-time signals which allows for a low complexity decoder. Within this class, space-time constellations based on the threaded algebraic space-time (TAST) architecture are considered. These constellations achieve the optimal diversity-versus-rate tradeoff over noncoherent block-fading channels and outperform previously proposed codes in the considered scenarios as demonstrated by the numerical results. Using the analytical and numerical results developed in this paper, nonunitary space-time codes are argued to offer certain advantages in block-fading channels where the appropriate use of coherent space-time codes is shown to offer a very efficient solution to the noncoherent space-time communication paradigm.

In this paper, we consider dense wireless sensor networks deployed to observe multiple random processes. The requirement is to reconstruct an estimate of each random process at the corresponding collector node. This leads to multiple many-to-one data gathering wireless channels that interfere with one another. We derive the transport capacity that the network can provide to each process and characterize an achievable rate region for the dense multimodal network. We further investigate the number of processes that can be observed simultaneously by the network. Specifically, we show that it is possible to observe O (N/sup /spl beta//) processes simultaneously such that the transport capacity scales as /spl Theta/ (log (N)) for each of the observed processes, with a large number of sensors A; and a fixed total average power. We show this result using a simple scheme based on antenna sharing. We then proceed to show that it is possible to simultaneously observe O (N/sup /spl beta//) continuous, spatially bandlimited Gaussian processes using a fixed total average power, through a scheme composed of single dimensional quantization, distributed Slepian-Wolf source coding, and the proposed antenna sharing strategy.

Minimum mean square error generalized decision-feedback equalizer (MMSE-GDFE) lattice decoding is shown to be an efficient decoding strategy for under-determined linear channels. The proposed algorithm consists of an MMSE-GDFE front-end followed by a lattice reduction algorithm with a greedy ordering technique and, finally, a lattice search stage. By introducing flexibility in the termination strategy of the lattice search stage, we allow for trading performance for a reduction in the complexity. The proposed algorithm is shown, through experimental results in MIMO quasistatic channels, to offer significant gains over the state of the art decoding algorithms in terms of performance enhancement and complexity reduction. On the one hand, when the search is pursued until the best lattice point is found, the performance of the proposed algorithm is shown to be within a small fraction of a dB from the maximum likelihood (ML) decoder while offering a large reduction in complexity compared to the most efficient implementation of ML decoding proposed by Dayal and Varanasi (e.g., an order of magnitude in certain representative scenarios). On the other hand, when the search is terminated after the first point is found, the algorithm only requires linear complexity while offering significant performance gains (in the order of several dBs) over the linear complexity algorithm proposed recently by Yao and Wornell.

In this paper, we introduce the class of lattice space-time (LAST) codes. We show that these codes achieve the optimal diversity-vs-multiplexing tradeoff defined by Zheng and Tse under generalized minimum Euclidean distance lattice decoding. Our scheme is based on a generalization of Erez and Zamir mod-/spl Lambda/ scheme to the MIMO case. This result settles the open problem posed by Zheng and Tse on the construction of explicit coding and decoding schemes that achieve the optimal diversity-vs-multiplexing tradeoff. Moreover, our results shed more light on the structure of optimal coding/decoding techniques in delay limited MIMO channels. In particular: 1) we show that MMSE-GDFE plays a fundamental role in approaching the limits of delay limited MIMO channels in the high SNR regime, unlike the AWGN channel case and 2) our random coding arguments represent a major departure from traditional space-time code designs based on the rank and/or mutual information design criteria.

In this paper, we propose novel cooperative transmission protocols for delay limited coherent fading channels consisting of N (half-duplex and single-antenna) partners and one cell site. In our work, we differentiate between the cooperative relay, broadcast, and multiple-access channels. The proposed protocols are evaluated using the Zheng-Tse diversity-multiplexing tradeoff. For the relay channel, we investigate two classes of cooperation schemes; namely, amplify and forward (AF) and decode and forward (DF). For the first class, we propose a new AF protocol and show it to outperform the space-time coded protocol of Laneman and Wornell without requiring decoding/encoding at the relays. For the class of DF protocols, we develop a dynamic decode and forward (DDF) protocol that achieves the optimal tradeoff for multiplexing gains 0 /spl les/ r /spl les/ 1/N. Furthermore, with a single relay, the DDF protocol is shown to dominate the class of AF protocols for all multiplexing gains. The superiority of the DDF protocol is shown to be more significant in the cooperative broadcast channel. The situation is reversed in the cooperative multiple-access channel where we propose a new AF protocol that achieves the optimal tradeoff for all multiplexing gains. A distinguishing feature of the proposed protocols in the three scenarios is that they do not rely on orthogonal subspaces, allowing for a more efficient use of resources.

We consider wireless sensor networks deployed to observe arbitrary random fields. The requirement is to reconstruct an estimate of the random field at a certain collector node. This creates a many-to-one data gathering wireless channel. One of the main challenges in this scenario is that the source/channel separation theorem, proved by Shannon for point-to-point links, does not hold any more. In this paper, we construct novel cooperative source-channel coding schemes that exploit the wireless channel and the correlation between the sources. In particular, we differentiate between two distinct cases. The first case assumes that the sensor nodes are equipped with receivers and, hence, every node can exploit the wireless link to distribute its information to its neighbors. We then devise an efficient deterministic cooperation strategy where the neighboring nodes act as virtual antennas in a beamforming configuration. The second, and more challenging, scenario restricts the capability of sensor nodes to transmit only. In this case, we argue that statistical cooperative source-channel coding techniques still yield significant performance gains in certain relevant scenarios. Specifically, we propose a low complexity cooperative source-channel coding scheme based on the proper use of low-density generator matrix codes. This scheme is shown to outperform the recently proposed joint source-channel coding scheme (Garcia-Frias et al., 2002) in the case of highly correlated sources. In both the deterministic and statistical cooperation scenarios, we develop analytical results that guide the optimization of the proposed schemes and validate the performance gains observed in simulations.

In this letter, we investigate the design of adaptive space-time codes that exploit partial transmitter channel state information (CSI). We introduce the adaptive space-time parsing paradigm as a generalization of the transmitter selection-diversity approach. We then use this new framework to construct full-diversity adaptive space-time codes for delay-limited applications with fixed-rate transmission. The proposed codes allow for reduced-complexity decoders and are robust to inaccuracies in the transmitter CSI.

This paper considers communication over coherent multiple-input multiple-output (MIMO) flat-fading channels where the channel is only known at the receiver. For this setting, we introduce the class of LAttice Space-Time (LAST) codes. We show that these codes achieve the optimal diversity-multiplexing tradeoff defined by Zheng and Tse under generalized minimum Euclidean distance lattice decoding. Our scheme is based on a generalization of Erez and Zamir mod-Lambda scheme to the MIMO case. In our construction the scalar "scaling" of Erez-Zamir and Costa Gaussian "dirty-paper" schemes is replaced by the minimum mean-square error generalized decision-feedback equalizer (MMSE-GDFE). This result settles the open problem posed by Zheng and Tse on the construction of explicit coding and decoding schemes that achieve the optimal diversity-multiplexing tradeoff. Moreover, our results shed more light on the structure of optimal coding/decoding techniques in delay-limited MIMO channels, and hence, open the door for novel approaches for space-time code constructions. In particular, 1) we show that MMSE-GDFE plays a fundamental role in approaching the limits of delay-limited MIMO channels in the high signal-to-noise ratio (SNR) regime, unlike the additive white Gaussian noise (AWGN) channel case and 2) our random coding arguments represent a major departure from traditional space-time code designs based on the rank and/or mutual information design criteria.

We consider the design of space-time codes for multiple-input multiple-output (MIMO) systems operated in the presence of co-channel interference (CCI). Based on the pairwise probability of error analysis, we develop a new design criterion that determines the code robustness to CCI (CCI diversity gain). We further develop an algebraic framework for constructing space-time codes that jointly optimize the fading and CCI diversity gains. The proposed framework is general for arbitrary numbers of transmit antennas and quadrature amplitude modulation constellations. Numerical results that quantify the performance gains offered by the proposed techniques are also presented.

The diversity-vs-rate tradeoffs of linear space-time constellations are derived and analyzed under different constraints on the receiver complexity, and the rate scaling with the signal-to-noise ratio (multiplexing gain). New constellations from the threaded algebraic space-time (TAST) signaling framework are matched to the receiver in the sense of achieving the optimal diversity-vs-rate tradeoffs for a given complexity of the sphere decoder or the nulling and cancellation receiver.

Significant performance gains can be leveraged in wireless networks by allowing the different nodes to cooperate. Cooperative transmission strategies attempt to realize the performance gains possible in multi-input multi-output (MIMO) fading channels by modeling the cooperating nodes as virtual antennas. However, in contrast to the point-to-point MIMO scenario, efficient cooperative schemes must address the distributed implementation challenge. For example, individual cooperating nodes may not be aware of their partners. We formulate the problem of maximizing the diversity advantage subject to the constraint of unknown message state information at the cooperating transmitter(s). We argue that our formulation can be used to model different relevant scenarios in wireless networks (e.g., fault tolerant applications, energy efficient sensor networks). In this setting, we propose a novel space-time filtering (STF) approach that achieves the optimal tradeoff between diversity advantage and receiver complexity. We further compare this approach with existing space-time coding approaches, highlighting the benefits of STF in the distributed implementation setting. Our arguments are supported by simulation results that demonstrate the performance gains possible with the proposed scheme in certain representative scenarios.

A new algebraic formulation for the diversity advantage design criterion for arbitrary space-time signals in noncoherent block fading channels is developed. It is shown that the new criterion encompasses, as a special case, the well-known diversity advantage criterion for unitary space-time signaling. Using the proposed criterion, the optimal diversity-vs-rate tradeoff is derived for training based noncoherent signaling schemes. Our results are then specialized to the class of affine space-time signals which allow for an efficient polynomial complexity decoder. Within this class, new space-time constellations based on the threaded algebraic space-time (TAST) framework are proposed. These codes achieve the optimal diversity-vs-rate tradeoff and outperform previously proposed codes in the considered scenarios as demonstrated by numerical results. Using these analytical and numerical results, we argue that non-unitary space-time codes offer certain advantages in block fading channels and the appropriate use of coherent space-time codes is shown to offer a very efficient solution to the noncoherent space-time communication paradigm.

Space-time constellations that are linear over the field of complex numbers are considered. Relevant design criteria for these constellations are summarized and some fundamental limits to their achievable performances are established. A new family of constellations that achieve optimal or near optimal performance with respect to the different criteria is presented. The proposed constellations belong to the threaded algebraic space-time signaling framework and achieve the optimal minimum squared Euclidean distance and the optimal delay in addition to the full rate, full diversity properties. For systems with one receive antenna, these constellations also achieve the optimal peak-to-average power ratio for QAM and PSK input constellations, as well as optimal coding gains in certain scenarios. The framework is general for any number of transmits and receives antennas and allow for realizing the optimal tradeoff between multiplexing rate and diversity.

In this paper, we consider the design of space-time codes for multi-input multi-output systems operated in the presence of co-channel interference (CCI). In particular, we consider two different scenarios. In the first, the channel state information (CSI) is assumed to be known only at the receiver. Based on the pairwise probability of error analysis, we develop a new design criterion that determines the code robustness to co-channel interference (CCI diversity gain). We further develop an algebraic framework for constructing space-time codes that jointly optimize the fading and CCI diversity gains. The proposed framework is general for arbitrary numbers of transmit antennas and quadrature amplitude modulation (QAM) constellations. In the second scenario, we investigate adaptive space-time techniques that exploit partial CSI at the transmitter. Our proposed design combines appropriate transmit antenna selection with adaptive rate and power allocation to combat both multi-path fading and CCI.

Diversity-vs-rate tradeoffs of linear space-time constellations are investigated under different constraints on the peak power, receiver complexity, and rate scaling with the signal-to-noise ratio (multiplexing gain). New constellations from the threaded algebraic space-time (TAST) signaling framework are shown to achieve the optimal tradeoffs.

We characterize the scaling laws of many-to-one dense wireless sensor networks and derive conditions governing the observability of random fields by such networks. We further extend our results to the multimodal case where the sensors observe multiple random processes simultaneously. Quite interestingly, our results show that an unbounded number of spatially bandlimited Gaussian processes can be observed simultaneously by a dense multimodal wireless sensor network.

In this letter, we present a simple generalization of the maximum ratio combining principle for space-time coded systems. This result leads to a maximum-likelihood decoder implementation that does not depend on the number of receive antennas and avoids the loss in performance incurred in the decoders proposed by Tarokh and Lo (1998) and Biglieri et al. The insights offered by this decoding rule allow for a simple and elegant proof for the space-time code design criterion in systems with large number of receive antennas. We further present an upper bound on probability of error that captures the dependence of space-time code design on the number of receive antennas. Finally, we present a computationally efficient approach for constructing space-time trellis codes that exhibit satisfactory performance in systems with variable number of receive antennas.

We consider the design of space-time overlays to upgrade single-antenna wireless communication systems to accommodate multiple transmit antennas efficiently. We define the overlay constraint such that the signal transmitted from the first antenna in the upgraded system is the same as that in the single-antenna system. The signals transmitted from the remaining antennas are designed according to space-time coding principles to achieve full spatial diversity in quasi-static flat fading channels. For both binary phase-shift keying (BPSK) and quaternary phase-shift keying modulation systems, we develop an algebraic design framework that exploits the structure of existing single-dimensional convolutional codes in designing overlays that achieve full spatial diversity with minimum additional decoding complexity at the receiver. We also investigate a concatenated coding approach for a BPSK overlay design in which the inner code is an orthogonal block code. This approach is shown to yield near optimal asymptotic performance for quasi-static fading channels. We conclude by offering a brief discussion outlining the extension of the proposed techniques to time-varying block fading channels.

Space-time (ST) constellations that are linear over the field of complex numbers are considered. Relevant design criteria for these constellations are summarized and some fundamental limits to their achievable performances are established. The fundamental tradeoff between rate and diversity is investigated under different constraints on the peak power, receiver complexity, and rate scaling with the signal-to-noise ratio (SNR). A new family of constellations that achieve optimal or near-optimal performance with respect to the different criteria is presented. The proposed constellations belong to the threaded algebraic ST (TAST) signaling framework, and achieve the optimal minimum squared Euclidean distance and the optimal delay. For systems with one receive antenna, these constellations also achieve the optimal peak-to-average power ratio for quadrature amplitude modulation (QAM) and phase-shift keying (PSK) input constellations, as well as optimal coding gains in certain scenarios. The framework is general for any number of transmit and receive antennas and allows for realizing the optimal tradeoff between rate and diversity under different constraints. Simulation results demonstrate the performance gains offered by the proposed designs in average power and peak power limited systems.

A simple and systematic approach for constructing full diversity m-dimensional constellations, carved from lattices over a number ring R, is proposed for an arbitrary dimension m. When R=Z[w/sub n/], the nth cyclotomic number ring, all the possible dimensions that allow for achieving the optimal minimum product distances using the proposed approach are determined. It turns out that one can construct optimal unitary transformations using our construction if and only if m factors into a power of 2 and powers of the primes dividing n. For m not satisfying these conditions, a method based on Diophantine approximation theory is proposed to "optimize" the minimum product distance. A lower bound on the product distance is given in this case, thus ensuring full diversity with "good" minimum product distances. Furthermore, the proposed approach subsumes the optimal unitary transformations proposed by Giraud et al. over R=Z[w/sub 4/] and R=Z[w/sub 3/], while giving optimal unitary transformations for infinitely many new values of n and m.

Maximum-likelihood (ML) decoding algorithms for Gaussian multiple-input multiple-output (MIMO) linear channels are considered. Linearity over the field of real numbers facilitates the design of ML decoders using number-theoretic tools for searching the closest lattice point. These decoders are collectively referred to as sphere decoders in the literature. In this paper, a fresh look at this class of decoding algorithms is taken. In particular, two novel algorithms are developed. The first algorithm is inspired by the Pohst enumeration strategy and is shown to offer a significant reduction in complexity compared to the Viterbo-Boutros sphere decoder. The connection between the proposed algorithm and the stack sequential decoding algorithm is then established. This connection is utilized to construct the second algorithm which can also be viewed as an application of the Schnorr-Euchner strategy to ML decoding. Aided with a detailed study of preprocessing algorithms, a variant of the second algorithm is developed and shown to offer significant reductions in the computational complexity compared to all previously proposed sphere decoders with a near-ML detection performance. This claim is supported by intuitive arguments and simulation results in many relevant scenarios.

A universal framework is developed for constructing full-rate and full-diversity coherent space-time codes for systems with arbitrary numbers of transmit and receive antennas. The proposed framework combines space-time layering concepts with algebraic component codes optimized for single-input-single-output (SISO) channels. Each component code is assigned to a "thread" in the space-time matrix, allowing it thus full access to the channel spatial diversity in the absence of the other threads. Diophantine approximation theory is then used in order to make the different threads "transparent" to each other. Within this framework, a special class of signals which uses algebraic number-theoretic constellations as component codes is thoroughly investigated. The lattice structure of the proposed number-theoretic codes along with their minimal delay allow for polynomial complexity maximum-likelihood (ML) decoding using algorithms from lattice theory. Combining the design framework with the Cayley transform allows to construct full diversity differential and noncoherent space-time codes. The proposed framework subsumes many of the existing codes in the literature, extends naturally to time-selective and frequency-selective channels, and allows for more flexibility in the tradeoff between power efficiency, bandwidth efficiency, and receiver complexity. Simulation results that demonstrate the significant gains offered by the proposed codes are presented in certain representative scenarios.

The availability of multiple transmit antennas allows for two-dimensional channel codes that exploit the spatial transmit diversity. These codes were referred to as space-time codes by Tarokh et al. (see ibid., vol.44, p.744-765, Mar. 1998) Most prior works on space-time code design have considered quasi-static fading channels. We extend our earlier work on algebraic space-time coding to block-fading channels. First, we present baseband design criteria for space-time codes in multi-input multi-output (MIMO) block-fading channels that encompass as special cases the quasi-static and fast fading design rules. The diversity advantage baseband criterion is then translated into binary rank criteria for phase shift keying (PSK) modulated codes. Based on these binary criteria, we construct algebraic space-time codes that exploit the spatial and temporal diversity available in MIMO block-fading channels. We also introduce the notion of universal space-time codes as a generalization of the smart-greedy design rule. As a part of this work, we establish another result that is important in its own right: we generalize the full diversity space-time code constructions for quasi-static channels to allow for higher rate codes at the expense of minimal reductions in the diversity advantage. Finally, we present simulation results that demonstrate the excellent performance of the proposed codes.

The authors introduced an algebraic design framework for space-time coding in flat-fading channels . We extend this framework to design algebraic codes for multiple-input multiple-output (MIMO) frequency-selective fading channels. The proposed codes strive to optimally exploit both the spatial and frequency diversity available in the channel. We consider two design approaches: The first uses space-time coding and maximum likelihood decoding to exploit the multi-path nature of the channel at the expense of increased receiver complexity. Within this time domain framework, we also propose a serially concatenated coding construction which is shown to offer a performance gain with a reasonable complexity iterative receiver in some scenarios. The second approach utilizes the orthogonal frequency division multiplexing technique to transform the MIMO multipath channel into a MIMO flat block fading channel. The algebraic framework is then used to construct space-frequency codes (SFC) that optimally exploit the diversity available in the resulting flat block fading channel. Finally, the two approaches are compared in terms of decoder complexity, maximum achievable diversity advantage, and simulated frame error rate performance in certain representative scenarios.

A novel framework is described here for constructing full rate, full diversity, and polynomial complexity space-time signals for systems with arbitrary numbers of transmit and receive antennas. By combining the space-time threading concepts with algebraic number theoretic constellations, we construct universal codes for scenarios where the channel state information (CSI) is known a-priori at the transmitter and receiver (TR-CSI), receiver only (R-CSI), and neither one of them (N-CSI).

We consider the design of space-time overlays to upgrade single antenna wireless communication systems to efficiently accommodate multiple transmit antennas. We define the overlay constraint such that the signal transmitted from the first antenna in the upgraded system is the same as that in the single antenna system. The signals transmitted from the remaining antennas are designed according to space-time coding principles to achieve full spatial diversity in quasi-static flat fading channels. For both BPSK and QPSK modulated systems, we develop an algebraic design framework that exploits the structure of existing single dimensional convolutional codes in designing overlays that achieve full spatial diversity with minimum additional decoding complexity at the receiver. We also investigate a concatenated coding approach for BPSK overlay design in which the inner code is an orthogonal block code. This approach is shown to yield near optimal asymptotic performance for quasi-static fading channels.

In this paper, we consider the design of space-time overlays to upgrade single antenna wireless communication systems to accommodate multiple transmit antennas efficiently. We define the overlay constraint such that the signal transmitted from the first antenna in the upgraded system is the same as that in the single antenna system. The signals transmitted from the remaining antenna's are designed according to space-time coding principles to achieve full spatial diversity in quasi-static flat fading channels. For both BPSK and QPSK modulated systems, we develop an algebraic design framework that exploits the structure of existing single dimensional convolutional codes in designing overlays that achieve full spatial diversity with minimum additional decoding complexity at the receiver.

The problem of efficient utilization of the frequency spectrum for satellite systems is investigated; one which results as a consequence of highly crowding adjacent channels. An analytical characterization of the resulting interference channel is introduced and then exploited for interference cancellation. Two classes of cancelers are investigated. The first approach does not benefit from the forward error control (FEC) coding information which limits the performance gain. This motivates the second approach where a joint implementation of interference cancellation and decoding is developed using soft-input-soft-output (SISO) modules along with the iterative structure. It is shown that iterative interference cancellation techniques can achieve significant gains compared with the single-user matched filter receiver.

Hochwald et al.(see IEEE Trans. Inform. Theory, Nov. 2001) have recognized that arbitrarily reliable communication is possible in multiantenna systems with coding over only a single coherence interval. In particular, they showed that reliable communication is possible for all rates R/spl les/C/sub a/ with code words that extend over a single coherence interval when the number of transmit antennas and coherence interval (n,T)/spl rarr//spl infin/. They coined the names "autocoding" for this phenomenon and "autocapacity" for C/sub a/. They also proposed a signalling scheme based on random unitary matrices that achieves a significant fraction of this capacity. The main limitation, however, is that currently no decoder of reasonable complexity is known for this signalling scheme. We investigate the application of space-time layering to autocoding. We show that properly constructed layered systems can achieve the autocapacity with a reasonable complexity receiver composed of minimum mean-square error (MMSE) decision feedback multiuser detectors and single user decoders. In addition to this asymptotic result, we propose a specific layering approach, the threaded space-time layering, that combines generalized bit interleaved space-time coded modulation, iterative signal processing and pilot symbol assisted channel estimation. We show that this approach is well suited for practical systems with limited numbers of transmit antennas and small coherence intervals. Finally, we report simulation results that demonstrate the ability of the threaded approach to achieve significant fractions of the autocapacity with a realizable receiver. The simulation results also indicate significant performance gains over the Cayley differential space-time signalling scheme in certain scenarios.

An iterative algorithm for joint decoding and channel estimation in frequency-hopping (FH) networks is proposed. In the proposed algorithm, soft decoder outputs are used in the iterative estimation of the time-varying variance of the additive interference resulting from the sum of the thermal noise, partial-band noise jamming, and other-user interference. The soft outputs are also used in the estimation of the independent random carrier phases and multiplicative Rayleigh fading coefficients in different frequency dwells. The estimation process is further enhanced through the insertion of known symbols in the transmitted data stream. The proposed iterative symbol-aided demodulation scheme is compared with the coherent scenario, where the channel state information is assumed to be known a priori at the receiver, for both convolutionally coded and turbo coded FH systems. The proposed iterative channel estimation approach is suited for slow FH systems where the channel dynamics are much slower than the hopping rate. This observation motivates the consideration of another robust approach for generating the log-likelihood ratios for fast hopping systems in additive white Gaussian noise channels. Simulation results that demonstrate the excellent performance of the proposed algorithms in various scenarios are also presented.

The authors previously developed an algebraic approach to space-time code design that unifies most of the known results on trellis space-time codes and opens the door for more sophisticated space-time code constructions. We present algebraic constructions for trellis and block space-time codes for BPSK and QPSK modulated systems. The new designs benefit from the algebraic approach and are general for arbitrary number of transmit antennas in quasistatic fading channels. We also provide simulation results comparing the frame error rate performance of various constructions. These simulation results establish the performance advantage achieved by algebraic space-time codes compared to previously known codes in various scenarios.

Demodulation and decoding for frequency-hopped spread-spectrum multiple-access (FH/SSMA) systems have been traditionally conducted by conventional single-user (noncollaborative) demodulation and error- and erasure-correcting decoding techniques. In this paper, we study the demodulation and decoding aspects of collaborative multiuser reception for FH/SSMA and propose methods which increase the number of users the system can support. In particular, we propose and analyze the optimum maximum a priori probability demodulation of multiple symbols or type, and the use of iterative multiuser decoding after the demodulation. Since hits from one or two other users are the most likely hit events in FH/SSMA, the joint demodulation of two or of three users is performed based on likelihood ratio tests. M-ary frequency-shift keying modulation with noncoherent demodulation and Reed-Solomon codes with hard-decision minimum distance decoding are used in the FH/SSMA system. Results are derived for both synchronous and asynchronous frequency-hop systems. The performance of the proposed multiuser detector in additive white Gaussian noise and flat Rayleigh fading channels is evaluated. Scenarios when all simultaneous users or only a subset of them are collaboratively demodulated and decoded are simulated.

We introduce a simple technique for analyzing the iterative decoder that is broadly applicable to different classes of codes defined over graphs in certain fading as well as additive white Gaussian noise (AWGN) channels. The technique is based on the observation that the extrinsic information from constituent maximum a posteriori (MAP) decoders is well approximated by Gaussian random variables when the inputs to the decoders are Gaussian. The independent Gaussian model implies the existence of an iterative decoder threshold that statistically characterizes the convergence of the iterative decoder. Specifically, the iterative decoder converges to zero probability of error as the number of iterations increases if and only if the channel E/sub b//N/sub 0/ exceeds the threshold. Despite the idealization of the model and the simplicity of the analysis technique, the predicted threshold values are in excellent agreement with the waterfall regions observed experimentally in the literature when the codeword lengths are large. Examples are given for parallel concatenated convolutional codes, serially concatenated convolutional codes, and the generalized low-density parity-check (LDPC) codes of Gallager and Cheng-McEliece (1996). Convergence-based design of asymmetric parallel concatenated convolutional codes (PCCC) is also discussed.

The information-theoretic capacity of multiple antenna systems has been shown to be significantly higher than that of single antenna systems in Rayleigh-fading channels. In an attempt to realize this capacity, Foschini (1996) proposed the layered space-time architecture. This scheme was argued to asymptotically achieve a lower bound on the capacity. Another line of work has focused on the design of channel codes that exploit the spatial diversity provided by multiple transmit antennas (Tarokh et al. 1998, Hammons and Gamal 2000). In this paper, we take a fresh look at the problem of designing multiple-input-multiple-output (MIMO) wireless systems. First, we develop a generalized framework for the design of layered space-time systems. Then, we present a novel layered architecture that combines efficient algebraic code design with iterative signal processing techniques. This novel layered system is referred to as the threaded space-time (TST) architecture. The TST architecture provides more flexibility in the tradeoff between power efficiency, bandwidth efficiency, and receiver complexity. It also allows for exploiting the temporal diversity provided by time-varying fading channels. Simulation results are provided for the various techniques that demonstrate the superiority of the proposed TST architecture over both the diagonal layered space-time architecture in Foschini (1996) and the multilayering approach (Tarokh et al. (1999).

The problem of efficient utilization of the frequency spectrum for coded satellite systems is investigated; one which results as a consequence of highly crowding adjacent channels. An analytical characterization of the resulting interference channel is introduced based on concepts in statistical decision theory and is then exploited for interference cancellation. A joint implementation of MMSE interference cancellation and forward error control (FEC) decoding is considered where soft-input soft-output (SISO) modules are used along with the iterative structure. It is shown that, for example, one can operate a satellite system with convolutionally encoded QPSK modulation that uses practical pulse shaping at the channel spacing valve of 0.75 of the symbol rate, or bandwidth efficiency level of 2.67 bits-per-second/Hz, with minimum additional energy requirement. (This corresponds to a spectral efficiency improvement of 55% compared with a conservative baseline system.).

The authors previously presented a new space-time architecture combining generalized layered transmission, advanced iterative multi-user detection techniques, and space-time code design that provides superior performance compared to the layered architectures proposed by Foschini (1996) and Tarokh et al. (see IEEE Trans. on Information Theory, vol.IT-44, p.744-65, 1998). We discuss the design of algebraic space-time codes for layered and non-layered architectures. We present new constructions for the quasi-static and block fading channels that extend to the diagonal transmission architecture proposed for differentially coherent space-time coding.

A new iterative receiver for joint detection and decoding of code division multiple access (CDMA) signals is presented. The new scheme is based on a combination of the minimum mean square error (MMSE) criterion and the turbo processing principle by Hagenauer (see Proc. Int. Symp. Turbo Codes and Related Topics, Brest, France, p.1-9, 1997). The complexity of the new scheme is of polynomial order in the number of users. The new scheme is applicable to two situations: (a) when the receiver is capable of decoding the signals from all users and (b) when the receiver is only capable of decoding the signals from a subset of users. In the first scenario, we establish that the proposed receiver achieves superior performance to the iterative soft interference cancellation technique under certain conditions. On the other hand, in the second scenario, we argue that the proposed receiver outperforms both the iterative soft interference canceler and the iterative maximum a posteriori (MAP) receiver because of its superior near-far resistance. For operation over fading channels, the estimation of the complex fading parameters for all users becomes an important ingredient in any multiuser detector. In our scheme, the soft information provided by the decoders is used to enhance this estimation process. Two iterative soft-input channel estimation algorithms are presented: the first is based on the MMSE criterion, and the second is a lower-complexity approximation of the first. The proposed multiuser detection algorithm(s) are suitable for both terrestrial and satellite applications of CDMA.

The design of space-time codes to achieve full spatial diversity over fading channels has largely been addressed by handcrafting example codes using computer search methods and only for small numbers of antennas. The lack of more general designs is in part due to the fact that the diversity advantage of a code is the minimum rank among the complex baseband differences between modulated codewords, which is difficult to relate to traditional code designs over finite fields and rings. We present general binary design criteria for PSK-modulated space-time codes. For linear BPSK/QPSK codes, the rank of (binary projections of) the unmodulated codewords, as binary matrices over the binary field, is a sufficient design criterion: full binary rank guarantees full spatial diversity. This criterion accounts for much of what is currently known about PSK-modulated space-time codes. We develop new fundamental code constructions for both quasi-static and time-varying channels. These are perhaps the first general constructions-other than delay diversity schemes-that guarantee full spatial diversity for an arbitrary number of transmit antennas.

We present a frequency hopping multiple-access concept suitable for multi-cell network architectures. A set of orthogonal frequency hopping (FH) patterns is assigned to the users in each cell and cells are differentiated by concatenating the user FH pattern with a shuffling sequence of the same hop rate. The use of guard times enables synchronous operation for the range of hopping rates of interest. The capacities of this network for the above FH/SS multiple access scheme with either coherent BPSK modulation or non-coherent BFSK modulation are evaluated for the AWGN channel. The effect of power control errors on the system performance is accounted for in each case. Similar results for asynchronous DS/SS cellular network (reverse link) are also reported for comparison purpose. The comparison is then extended to the Rayleigh fading channel. It is argued that synchronous FH/SSMA is implementable and can provide higher capacity than asynchronous DS/CDMA under certain conditions.

We investigate the application of joint decoding and channel estimation for DS/CDMA transmission over slow Rayleigh fading channels. Some known symbols are inserted in the encoded data stream to enhance the channel estimation process. An iterative algorithm that uses the decoding information, in addition to the information contained in the known symbols, to improve the channel parameters estimate is proposed. A is shown that the optimum scheme has a complexity which grows exponentially with the channel estimation filter length. Hence, we propose some alternative sub-optimum schemes with polynomial complexity. The different techniques that provide a tradeoff between simplicity of implementation and BER performance are compared.