We will be discussing the following paper:

Abolfazl Motahari, Guy Bresler and David Tse, "Information Theory of DNA Sequencing," available on ArXiv: 1203.6233.

Abstact: DNA sequencing is the basic workhorse of modern day biology and medicine. Shotgun sequencing is the dominant technique used: many randomly located short fragments called reads are extracted from the DNA sequence, and these reads are assembled to reconstruct the original sequence. A basic question is: given a sequencing technology and the statistics of the DNA sequence, what is the minimum number of reads required for reliable reconstruction? This number provides a fundamental limit to the performance of any assembly algorithm. By drawing an analogy between the DNA sequencing problem and the classic communication problem, we formulate this question in terms of an information theoretic notion of sequencing capacity. This is the asymptotic ratio of the length of the DNA sequence to the minimum number of reads required to reconstruct it reliably. We compute the sequencing capacity explicitly for a simple statistical model of the DNA sequence and the read process. Using this framework, we also study the impact of noise in the read process on the sequencing capacity.

We will be discussing the following paper:

Tiangao Gou, Syed A. Jafar, Sang-Woon Jeon, Sae-Young Chung, "Aligned Interference Neutralization and the Degrees of Freedom of the 2x2x2 Interference Channel," available on ArXiv: 1012.2350.

Abstact: We show that the 2x2x2 interference network, i.e., the multihop interference network formed by concatenation of two 2-user interference channels achieves the min-cut outer bound value of 2 DoF, for almost all values of channel coefficients, for both time-varying or fixed channel coefficients. The key to this result is a new idea, called aligned interference neutralization, that provides a way to align interference terms over each hop in a manner that allows them to be cancelled over the air at the last hop.

We will be discussing the following paper:

Andrew Sendonaris, Elza Erkip, and Behnaam Aazhang, "User Cooperation Diversity—Part I: System Description," IEEE Transactions on Communications, vol. 51, no. 11, Nov 2003.

Abstact: Mobile users’ data rate and quality of service are limited by the fact that, within the duration of any given call, they experience severe variations in signal attenuation, thereby necessitating the use of some type of diversity. In this two-part paper, we propose a new form of spatial diversity, in which diversity gains are achieved via the cooperation of mobile users. Part I describes the user cooperation strategy, while Part II focuses on implementation issues and performance analysis. Results show that, even though the interuser channel is noisy, cooperation leads not only to an increase in capacity for both users but also to a more robust system, where users’ achievable rates are less susceptible to channel variations.

We will be discussing the following paper:

H. Sung, S. Park, K. Lee and I. Lee, "Linear precoder designs for K-user interference channels," IEEE Transactions on Wireless Communications, Jan 2010.

Abstact: This paper studies linear precoding and decoding schemes for K-user interference channel systems. It was shown by Cadambe and Jafar that the interference alignment (IA) algorithm achieves a theoretical bound on degrees of freedom (DOF) for interference channel systems. Based on this, we first introduce a non-iterative solution for the precoding and decoding scheme. To this end, we determine the orthonormal basis vectors of each user's precoding matrix to achieve the maximum DOF, then we optimize precoding matrices in the IA method according to two different decoding schemes with respect to individual rate. Second, an iterative processing algorithm is proposed which maximizes the weighted sum rate. Deriving the gradient of the weighted sum rate and applying the gradient descent method, the proposed scheme identifies a local-optimal solution iteratively. Simulation results show that the proposed iterative algorithm outperforms other existing methods in terms of sum rate. Also, we exhibit that the proposed non-iterative method approaches a local optimal solution at high signal-to-noise ratio with reduced complexity.

Developing an effective cooperative spectrum sensing (CSS) scheme in Cognitive Radio (CR) network is necessary. In this talk, I’d like to discuss with research issues related to CCS such as how to reduce delay time for gathering sensing data in CCS, how to reduce transmission overhead in the control channel, how to be robust to malicious users, and how to combine local decisions without any requirement of priori network information. I also introduce a recent work titled by “Cluster-Based Selective Cooperative Spectrum Sensing in Cognitive Radio. The paper is attached to the announcement email.

We will be discussing the following paper:

Y. Tian and A. Yener, "Relaying for Multiuser Networks in the Absence of Codebook Information," submitted to IEEE Transactions on Information Theory, Jan 2012.

Abstract: This work considers relay assisted transmission for multiuser networks when the relay has no access to the codebooks used by the transmitters. The relay is called oblivious for this reason. Of particular interest is the generalized compress-and-forward (GCF) strategy, where the destinations jointly decode the compression indices and the transmitted messages, and their optimality in this setting. The relay-to-destination links are assumed to be out-of-band with finite capacity. Two models are investigated: the multiple access relay channel (MARC) and the interference relay channel (IFRC). For the MARC with an oblivious relay, a new outerbound is derived and it is shown to be tight by means of achievability of the capacity region using GCF scheme. For the IFRC with an oblivious relay, a new strong interference condition is established, under which the capacity region is found by deriving a new outerbound and showing that it is achievable using GCF scheme. The result is further extended to establish the capacity region of M-user MARC with an oblivious relay, and multicast networks containing M sources and K destinations with an oblivious relay.

We will be discussing the following paper:

C.U. Saraydar, N.B. Mandayam and D.J. Goodman, "Efficient power control via pricing in wireless data networks," IEEE Transactions on Communications, vol.50, no.2, pp.291-303, Feb 2002.

"It is a very important game-theoretic paper, with over 800 citations. Most importantly, the group members will have the opportunity to grasp the fundamental game-theoretic concepts such as Nash equilibrium and Pareto optimality, and its most common application for wireless communications - the distributed uplink power control for multiple access channel." -- Igor

We will be discussing the following paper:

Mohammad Ali Maddah-Ali and David Tse, "Completely Stale Transmitter Channel State Information is Still Very Useful," Forty-Eighth Annual Allerton Conference, UIUC, Illinois, September 2010.

Abstract: Transmitter channel state information (CSIT) is crucial for the multiplexing gains offered by advanced interference management techniques such as multiuser MIMO and interference alignment. Such CSIT is usually obtained by feedback from the receivers, but the feedback is subject to delays. The usual approach is to use the fed back information to predict the current channel state and then apply a scheme designed assuming perfect CSIT. When the feedback delay is large compared to the channel coherence time, such a prediction approach completely fails to achieve any multiplexing gain. In this paper, we show that even in this case, the completely stale CSI is still very useful. More concretely, we showed that in a MIMO broadcast channel with K transmit antennas and K receivers each with 1 receive antenna, K/(1+1/2+...+1/K) (> 1) degrees of freedom is achievable even when the fed back channel state is completely independent of the current channel state. Moreover, we establish that if all receivers have identically distributed channels, then this is the optimal number of degrees of freedom achievable. In the optimal scheme, the transmitter uses the fed back CSI to learn the side information that the receivers receive from previous transmissions rather than to predict the current channel state. Our result can be viewed as the first example of feedback providing a degree-of-freedom gain in memoryless channels.

Kaya and Ertugrul will be presenting the following papers:

Kaya Tutuncuoglu and Aylin Yener, Optimal Power Control for Energy Harvesting Transmitters in an Interference Channel, to appear in Proceedings of Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2011.

Ertugrul N. Ciftcioglu and Aylin Yener, Quality-of-Information Aware Transmission Policies with Time-Varying Links, to appear in IEEE Military Communications Conference (MILCOM) 2011, Baltimore, MD, November 2011.

We will be discussing the following paper:

Lizhong Zheng and David Tse, "Diversity and Multiplexing: A Fundamental Tradeoff in Multiple-Antenna Channels," IEEE Transactions on Information Theory, vol. 49, no. 5, May 2003.

Abstract: Multiple antennas can be used for increasing the amount of diversity or the number of degrees of freedom in wireless communication systems. In this paper, we propose the point of view that both types of gains can be simultaneously obtained for a given multiple-antenna channel, but there is a fundamental tradeoff between how much of each any coding scheme can get. For the richly scattered Rayleigh-fading channel, we give a simple characterization of the optimal tradeoff curve and use it to evaluate the performance of existing multiple antenna schemes.

We will be discussing the following paper:

Herbert Robbins and Sutton Monro, "A Stochastic Approximation Method," Annals of Mathematical Statistics 22, #3, pp. 400–407, September 1951.

Abstract: Let M(x) denote the expected value at level x of the response to a certain experiment. M(x) is assumed to be a monotone function of x but is unknown to the experimenter, and it is desired to find the solution x = \theta of the equation M(x) = \alpha, where \alpha is a given constant. We give a method for making successive experiments at levels x_1,x_2,... in such a way that x_n will tend to \theta in probability.

We will be discussing the following paper:

J. P. M. Schalkwijkand, T. Kailath, "A Coding Scheme for Additive Noise Channels with Feedback-Part I: No Bandwidth Constraint" IEEE Transactions on Information Theory, vol. IT-12, no. 2, Apr. 1966.

Abstract: In some communication problems, it is a good assumption that the channel consists of an additive white Gaussian noise forward link and an essentially noiseless feedback link. In this paper, we study channels where no bandwidth constraint is placed on the transmitted signals. Such channels arise in space communications. It is known that the availability of the feedback link cannot increase the channel capacity of the noisy forward link, but it can considerably reduce the coding effort required to achieve a given level of performance. We present a coding scheme that exploits the feedback to achieve considerable reductions in coding and decoding complexity and delay over what would be needed for comparable performance with the best known (simplex) codes for the one-way channel. Our scheme, which was motivated by the Robbins-Monro stochastic approximation technique, can also be used over channels where the additive noise is not Gaussian but is still independent from instant to instant. An extension of the scheme for channels with limited signal bandwidth is presented in a companion paper (Part II).

We will be discussing the following paper:

T. Philosof, R. Zamir, U. Erez and A. J. Khisti, "Lattice Strategies for the Dirty Multiple Access Channel," IEEE Transactions on Information Theory, August 2011.

Abstract: In Costa's dirty-paper channel, Gaussian random binning is able to eliminate the effect of interference which is known at the transmitter, and thus achieve capacity. We examine a generalization of the dirty-paper problem to a multiple access channel (MAC) setup, where structured (lattice-based) binning seems to be necessary to achieve capacity. In the dirty-MAC, two additive interference signals are present, one known to each transmitter but none to the receiver. The achievable rates using Costa's Gaussian binning vanish if both interference signals are strong. In contrast, it is shown that lattice-strategies (“lattice precoding”) can achieve positive rates, independent of the interference power. Furthermore, in some cases—which depend on the noise variance and power constraints—high-dimensional lattice strategies are in fact optimal. In particular, they are optimal in the limit of high SNR—where the capacity region of the dirty MAC with strong interference approaches that of a clean MAC whose power is governed by the minimum of the users' powers rather than their sum. The rate gap at high SNR between lattice-strategies and optimum (rather than Gaussian) random binning is conjectured to be ${1over 2}log_2(pi e/6)approx 0.254$ bit. Thus, the doubly dirty MAC is another instance of a network setting, like the Körner-Marton problem, where (linear) structured coding is potentially better than random binning.

We will be discussing the following paper:

S. A. Jafar, S. Shamai(Shitz), "Degree of freedom region for the MIMO X channel," IEEE Transactions on Information Theory, vol. 54, no. 1, January 2008.

Abstract: We provide achievability as well as converse results for the degrees of freedom region of a multiple-input multiple-output (MIMO) X channel, i.e., a system with two transmitters, two receivers, each equipped with multiple antennas, where independent messages need to be conveyed over fixed channels from each transmitter to each receiver. The inner and outer bounds on the degrees of freedom region are tight whenever integer degrees of freedom are optimal for each message.With M = 1 antennas at each node, we find that the total (sum rate) degrees of freedom are bounded above and below as 1 < eta_X < 4/3. If M > 1 and channel matrices are nondegenerate then the precise degrees of freedom eta_X = 4/3 M. Thus, the MIMO X channel has noninteger degrees of freedom when M is not a multiple of 3. Simple zero forcing without dirty paper encoding or successive decoding, suffices to achieve the 4/3 M degrees of freedom. If the channels vary with time/frequency then the X channel with single antennas (M = 1) at all nodes has exactly 4/3 degrees of freedom. The key idea for the achievability of the degrees of freedomis interference alignment—i.e., signal spaces are aligned at receivers where they constitute interference while they are separable at receivers where they are desired.We also explore the increase in degrees of freedomwhen some of themessages are made available to a transmitter or receiver in the manner of cognitive radio.

We will continue discussing the following paper:

X. Kang, R. Zhang and M. Motani, "Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach," Arxiv preprint arXiv:1103.2240, 2011.

We will be discussing the following paper:

X. Kang, R. Zhang and M. Motani, "Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach," Arxiv preprint arXiv:1103.2240, 2011.

Abstract: This paper investigates the price-based resource allocation strategies for the uplink transmission of a spectrum-sharing femtocell network, in which a central macrocell is underlaid with distributed femtocells, all operating over the same frequency band as the macrocell. Assuming that the macrocell base station (MBS) protects itself by pricing the interference from the femtocell users, a Stackelberg game is formulated to study the joint utility maximization of the macrocell and the femtocells subject to a maximum tolerable interference power constraint at the MBS. Especially, two practical femtocell channel models: sparsely deployed scenario for rural areas and densely deployed scenario for urban areas, are investigated. For each scenario, two pricing schemes: uniform pricing and non-uniform pricing, are proposed. Then, the Stackelberg equilibriums for these proposed games are studied, and an effective distributed interference price bargaining algorithm with guaranteed convergence is propsed for the uniform-pricing case. Finally, numerical examples are presented to verify the proposed studies. It is shown that the proposed algorithms are effective in resource allocation and macrocell protection requiring minimal network overhead for spectrum-sharing-based two-tier femtocell networks.

We will be discussing the following paper:

Z. Charbiwala, S. Zahedi, Y. Kim, M.B. Srivastava, Y.H. Cho, "Toward Quality of Information Aware Rate Control for Sensor Networks," Fourth International Workshop on Feedback Control Implementation and Design in Computing Systems and Networks, 2009.

Abstract: In sensor networks, it is the Quality of Information (QoI) delivered to the end user that is of primary interest. In general, measurements from different sensor nodes do not contribute equally to the QoI because of differing sensing modalities, node locations, noise levels, sensing channel conditions, fault status, and physical process dynamics. In addition, metrics of QoI are highly application dependent, such as probability of detection of an event or fidelity of reconstruction of a spatio-temporal process. Despite these considerations, traditional data dissemination protocols in sensor networks have been designed with a focus on metrics such as throughput, packet delivery ratio, latency, and fair division of bandwidth, and are thus oblivious to the importance and quality of sensor data and the target application. In this paper, we argue for sensor network protocols that are cognizant of and use feedback from the sensor fusion algorithms to explicitly optimize for application-relevant QoI metrics during network resource allocation decisions. Through analysis and simulation we demonstrate the application-level performance benefits accruing from such a QoI-aware approach to network resource management in the context of a centralized sensor rate selection mechanism for an event detection application scenario.

We will be discussing the following paper:

T. Weissman, "Capacity of Channels with Action-Dependent States," IEEE Transactions on Information Theory, vol.56, no.11, pp.5396-5411, Nov. 2010.

Abstract: We consider channels with action-dependent states: Given the message to be communicated, the transmitter chooses an action sequence that affects the formation of the channel states, and then creates the channel input sequence based on the state sequence. We characterize the capacity of such a channel both for the case where the channel inputs are allowed to depend non-causally on the state sequence and the case where they are restricted to causal dependence. Our setting covers previously considered scenarios involving transmission over channels with states known at the encoder, as well as various new coding scenarios for channels with a ‘rewrite’ option that may arise naturally in storage for computer memories with defects or in magnetic recoding. A few examples are worked out in detail.

This work considers Quality-of-Information (QoI) aware rate allocation policies for multiple access channels. QoI is a recently introduced composite metric which is impacted by a number of attributes including accuracy and timeliness of delivery of information communicated from the source(s) to the destination(s), and as such differs from traditional quality-of-service metrics considered to date. The focus of this work is defining the Operational Information Content Sum Capacity (OICC-S) of a network, as the set of QoI-vectors supported which maximize sum utility of the system. This utility is defined as a function of the QoI attributes provided by the source input, as well as the channel induced attributes that impact the QoI delivered to the destination(s). Optimum rate allocation to maximize the output sum utility and achieve OICC-S of the network is provided, and demonstrated to differ from the solution that provides maximum throughput. Finally, we discuss dynamic QoI-adaptation policies for time-varying links, as well as QoI-aware scheduling schemes for multihop relay networks.

We will be discussing the following paper:

Mochaourab, R.; Jorswieck, E.A.;, "Optimal Beamforming in Interference Networks with Perfect Local Channel Information," IEEE Transactions on Signal Processing, vol.59, no.3, pp.1128-1141, March 2011.

Abstract: We consider settings in which T multi-antenna transmitters and K single-antenna receivers concurrently utilize the available communication resources. Each transmitter sends useful information only to its intended receivers and can degrade the performance of unintended systems. Here, we assume the performance measures associated with each receiver are monotonic with the received power gains. In general, the joint performance of the systems is desired to be Pareto optimal. However, designing Pareto optimal resource allocation schemes is known to be difficult. In order to reduce the complexity of achieving efficient operating points, we show that it is sufficient to consider rank-1 transmit covariance matrices and propose a framework for determining the efficient beamforming vectors. These beamforming vectors are thereby also parameterized by T(K-1) real-valued parameters each between zero and one. The framework is based on analyzing each transmitter's power gain-region which is composed of all jointly achievable power gains at the receivers. The efficient beamforming vectors are on a specific boundary section of the power gain-region, and in certain scenarios it is shown that it is necessary to perform additional power allocation on the beamforming vectors. Two examples which include broadcast and multicast data as well as a cognitive radio application scenario illustrate the results.

This talk is the continuation of last week's talk, focusing on the paper below:

Sung Hoon Lim; Young-Han Kim; El Gamal, A.; Sae-Young Chung; , "Noisy network coding," Information Theory Workshop (ITW), 2010 IEEE , vol., no., pp.1-5, 6-8 Jan. 2010.

This talk is divided into two major parts.

In the first part, we together study the noisy network coding scheme recently proposed by Lim, Kim, El Gamal and Chung. The scheme is devised for sending multiple sources over a general noisy network. Three main techniques are involved in the proposed scheme: message repetition coding, relay signal compression, and simultaneous decoding. It is shown that the scheme unifies and extends previous results on network coding and its extensions, and on compress-and-forward for the relay channels. Specifically, I will explain how this coding scheme works in a conventional three-node relay channel.

In the second part, a state-dependent relay channel is studied in which strictly causal channel state information is available at the relay and no state information is available at the source and destination. The source and the relay are connected via two unidirectional out-of-band orthogonal links of finite capacity, and a state-dependent memoryless channel connects the source and the relay, on one side, and the destination, on the other. Via the orthogonal links, the source can convey information about the message to be delivered to the destination to the relay while the relay can forward state information to the source. This exchange enables cooperation between the source and the relay on transmission of message and state information to the destination. First, two achievable schemes are proposed that exploit both message and state cooperation. It is shown that a transmission scheme inspired by noisy network coding performs better than a strategy based on block Markov coding and backward decoding. Next, based on the given achievable schemes and appropriate upper bounds, capacity results are identified for some special cases. Finally, a Gaussian model is studied, along with corresponding numerical results that illuminate the relative merits of state and message cooperation.

Reference: Lim, S. H. and Kim, Y. H. and El Gamal, A. and Chung, S. Y., Noisy network coding, available online at http://arxiv.org/abs/1002.3188v2, 2010. (I recommend that we should read this paper at least up to Section III. )

This work studies the Gaussian interference channel (IC) with a relay, which transmits and receives in a band that is orthogonal to the IC. The channel associated with the relay is thus an out-of-band relay channel (OBRC). The focus is on a symmetric channel model, in order to understand the fundamental impact of the OBRC on the signal interaction of the IC, in the simplest possible setting. First, the linear deterministic model is investigated and the sum capacity of this channel is established for all possible channel parameters. In particular, it is observed that the impact of OBRC, as its links get stronger, is similar to that of output feedback for the IC. The insights obtained from the deterministic model are then used to design achievable schemes for the Gaussian model. The interference links are classified as extremely strong, very strong, strong, moderate, weak, and very weak. For strong and moderate interference, separate encoding is near optimal. For very strong and extremely strong interference, the interference links provide side information to the destinations, which can help the transmission through the OBRC. Specifically, when the interference is extremely strong, the channel acts as if there are two disjoint OBRCs helping each source-destination pair. For weak or very weak interference, we use the Han-Kobayashi scheme for the IC where the messages are split into common and private. We find that it is beneficial to further split the common message into two parts, and the OBRC plays an important role in decoding the common message. It is shown that our strategy achieves the symmetric capacity to within 1.14625 bits per channel use for all channel parameters.

The major motivation behind this presentation is to introduce you to my research experience. Thus, instead of elaborating on a single or a few topics (which is usually a good idea), I have decided to take the unconventional approach and cover most of my work, providing you with a motivation behind each of the topics, the basic approach I took to solve the problem and interesting conclusions (if any). The presentations is divided in two major parts (as is my research history), namely the Cooperative Retransmission Protocols and Distributed Resource Allocation (with applications of game theory). You will hear, among other topics, about the way that the circuitry consumption harms the energy efficiency in wireless networks (and how it can be solved), about the concepts of exchanging the spectrum for relaying services in cognitive radio, relaying-motivation approach and self-configurable interference-avoiding networks.

This will be the continuation of the last talk. (See below)

The topic of this talk is the fingerprinting games. The fingerprinting games are essentially designed for protecting the copyrighted software or content reliably to possible attacks. In order to ensure this protection, the distributor of the content digitally embeds a unique fingerprint in the content and knows which copy is given to which customer. If one of the customers try to distribute the content without authorization, then the distributor will detect that user. The problem gets complicated if some the users cooperate and attempt the unauthorized distribution using their fingerprint information. The several copies of the content give more information about the fingerprints, therefore pirates could change the content with leaving only weak traces. A two player zero-sum game is constructed to solve this problem. In this game, the distributor aims to maximize the number of users that a fingerprinting code can support and ensure the detection of the attackers. In contrast, the group of pirates aims to minimize this fingerprinting capacity. Saddle point solution is shown to be optimal for this fingerprinting game.

We investigate Quality of Information (QoI) aware scheduling in task processing networks. Specifically, we consider the scenario where a network sequentially receives tasks from an end user, utilizes its resources to process them, and sends back its response. The utility derived by the end user from this response depends on both the accuracy and the freshness of the information. There is often a tradeoff between these two attributes and we present a model that quantifies this dependence. Using dynamic programming and optimal stopping theory, we characterize the optimal scheduling policy that maximizes the time average utility delivered by the network. We show that for many scenarios of practical interest, the optimal policy has a simple threshold structure. We also propose a method to approximately compute the threshold in closed-form. This work takes a step towards incorporating application aware objectives in making optimal scheduling decisions.

The time-delay estimation problem is studied for cognitive radio systems, multiple-input single-output (MISO) systems, and cognitive single-input multiple-output (SIMO) systems. A two-step approach is proposed for cognitive radio and cognitive SIMO systems in order to perform time-delay estimation with significantly lower computational complexity than the optimal maximum likelihood (ML) estimator. In the first step of this two-step approach, an ML estimator is used for each receiver branch in order to estimate the unknown parameters of the signal received via that branch. Then, in the second step, the estimates from the first step are combined in various ways in order to obtain the final time-delay estimate. The combining techniques that are used in the second step are called optimal combining, signal-to-noise ratio (SNR) combining, selection combining, and equal combining. It is shown that the performance of the optimal combining technique gets very close to the Cramer-Rao lower bound (CRLB) at high SNRs. These combining techniques provide various mechanisms for diversity combining for time-delay estimation and extend the concept of diversity in communications systems to the time-delay estimation problem in cognitive radio and cognitive SIMO systems. Simulation results are presented to evaluate the performance of the proposed estimators and to verify the theoretical analysis. For the solution of the time-delay estimation problem in MISO systems, ML estimation based on a genetic global optimization algorithm, namely, differential evolution (DE), is proposed. This approach is proposed in order to decrease the computational complexity of the ML estimator, which results in a complex optimization problem in general. A theoretical analysis is carried out by deriving the CRLB. Simulation studies for Rayleigh and Rician fading scenarios are performed to investigate the performance of the proposed algorithm.

Energy harvesting from the environment significantly improves the lifetime of battery powered wireless nodes. However the unknown nature of the recharge process calls for transmission policies to adapt to this setting. Mainly, the average power constraint in traditional transmission problems is replaced with a set of energy constraints based on the stochastic energy arrivals and battery capacity. We set out to find optimal transmission policies for wireless transmitters with power control. We consider the two problems of throughput maximization until a deadline and transmission completion time minimization for a packet. A concave power-rate function is assumed, as the case in the AWGN channel. First, optimal offline power allocation policies are developed on a static channel with non-causally known energy arrivals, and the relationship between the two problems are shown. Then, the solution is extended to fading channels with an intuitive directional water-filling algorithm. Finally online algorithms using dynamic programming and other approaches are suggested.

A standard assumption in network information theory is that all nodes are informed at all times of the operations carried out (e.g., of the codebooks used) by any other terminal in the network. In this talk, information theoretic limits are presented under the assumption that, instead, some nodes are not informed about the codebooks used by other terminals. Specifically, capacity results are derived for a relay channel in which the relay is oblivious to the codebook used by the source (oblivious relaying), and an interference relay channel with oblivious relaying and in which each destination is possibly unaware of the codebook used by the interfering source (interference-oblivious decoding). Extensions are also discussed for a related scenario with standard codebook-aware relaying but interference-oblivious decoding.

We consider the linear deterministic model for the two user interference channel (IC) with an out-of-band relay (OBR). In this model, each user has access to two orthogonal bands, where one band forms the IC, and the other band is assisted by a half-duplex relay, i.e., the relay receives and transmits in orthogonal bands. The channel is assumed to be symmetric. We first derive new outerbounds using genie arguments, and then construct optimal relaying strategies. As a result, we characterize the sum capacity of this model for all channel parameters. In particular, it is shown that similar to the case of the IC with output feedback (and without a relay), the “W” curve for the sum capacity of the IC becomes “V” curve as the strength of the links in the OBRC grows. The interference links are classified as extremely strong, very strong, strong, moderate, weak, and very weak. For the IC without the relay, it is known that some signal spaces are left unused for the sum-capacity-optimal transmission strategy. We show that, with an OBR, these spaces can be utilized to achieve the sum capacity of this model improving upon that of the IC without the OBR. We show that for very strong and extremely strong interference, the interference is useful to improve the achievable rates. For weak or very weak interference, the unused signal spaces of the IC can be utilized to transmit new information bits.

Percolation theory was developed to model diffusion process in materials. In the recent years, several researchers have used the tools from percolation theory to analyze connectivity in wireless networks. This talk will present a brief introduction to percolation theory. Two applications of percolation theory to secrecy graphs will be presented. In the first example, we consider end-to-end secure communication in a large wireless network, where the locations of eavesdroppers are uncertain. Our framework attempts to bridge the gap between physical layer security under uncertain channel state information of the eavesdropper and network level connectivity under security constraints, by modeling location uncertainty directly at the network level as correlated node and link failures in a secrecy graph. In a secrecy graph, link connectivity is determined using information theoretic secrecy models. Bounds on the percolation threshold are obtained for square and triangular lattices, and bounds on mean degree are obtained for Poisson secrecy graphs. Both analytic and simulation results show the dramatic effect of uncertainty in location of eavesdroppers on connectivity in a secrecy graph. In the second example, we consider time-varying security failures and recoveries in a secrecy graph, where security is provided using cryptographic keys. Queuing theory is used to model the time-varying nature of security compromises, and percolation theory is used to analyze connectivity in the secrecy graph. Numerical results demonstrate that in order to obtain a low probability of connectivity outage, the system must be designed for a large probability of key recovery rather than a large average key recovery rate.

I will be presenting some issues of charging, rate control and congestion control for arbitrary networks with elastic traffic. I will first discuss the general idea of rate control, efficiency versus fairness and fairness criteria. Then I will focus on [1] which decomposes the optimization problem of throughput maximization of the system into distributed problems which can be solved at the users and the network manager. I will also try to touch upon the main ideas of [2] which models the network resource allocation as a game.

References:

[1] Kelly F.P. (1997) Charging and rate control in elastic traffic: European Transactions onTelecommunications.

[2] R. Johari and J. Tsitsiklis Efficiency Loss in a Network Resource Allocation Game Mathematics of Operations Research 29(3), 407-435, 2004.

The emerging next generation wireless systems have revealed the problem of poor indoor coverage and high capacity demand of indoor users. Apparently, studies show that most of the data transmission occurs indoor, which requires the highest data rate.

This talk will give a brief overview on HomeNodeBs (Home Base Stations), or femtocells, the data access points installed by home users to get better indoor coverage . The key technical problems of tiered cellular networks as well as problems arising from the ad-hoc nature of femtocells will be addressed. Recent research results about interference avoidance, coverage and access issues will be provided.

The previous presentation was an overview on the seminal results on information theoretic secrecy. It began with the motivation and definiton of of security in wiresless communication systems, continued with single antenna wiretap channel model where one sender is sending a confidential message to an intended receiver in the presence of an eavesdropper. Finally, the some of the studies on MIMO wiretap channels are presented.

This week, I will give a brief summary of the previous results and then focus on the paper listed in the references. Achievable rates and capacity achieving schemes for the Gaussian wiretap channels are studied in this paper when there are multiple transmit antennas at the sender, multiple receive antennas at the intended receiver and multiple antennas at the eavesdropper.

This talks will focus on the optimal system design and performance evaluation for cooperative spectrum sensing in cognitive radio networks. First we address optimal spectrum sensing in cognitive radio networks considering its system level cost that accounts for the local processing cost of sensing (sample collection and energy calculation at each secondary user) as well as the transmission cost (forwarding energy statistic from secondary users to fusion center). The optimization problem solves for the appropriate number of samples to be collected and amplifier gains at each secondary user to minimize the global error probability subject to a total cost constraint. In particular, closed-form expressions for optimal solutions are derived and a generalized water-filling algorithm is proposed when number of samples or amplifier gains are fixed and additional constraints are imposed. Furthermore, when jointly designing the number of samples and amplifier gains, optimal solution indicates that only one secondary user needs to be active, i.e., collecting samples for local energy calculation and transmitting energy statistic to fusion center.

Second, we investigate the system level performance evaluation for cooperative spectrum sensing in cognitive radio networks. Three performance criteria are quantitively analyzed for cooperative spectrum sensing. First, the average error probability is determined given fixed amplifier gains for a fixed number of secondary users by considering all possible channel realizations. Second, the asymptotic error probability is computed in a power constrained cognitive radio network when the number of secondary user approaches infinity. Third, the outage probability is examined when instantaneous error probability is greater than a predefined threshold.

We consider the problem of cross-layer resource allocation for wireless networks operating with rechargeable batteries under general arrival, channel state and recharge processes. The objective is to maximize total system utility, defined as a function of the long-term rate achieved per link, while satisfying energy and power constraints. A policy with decoupled admission control and power allocation decisions is proposed that achieves asymptotic optimality for sufficiently large battery capacity to maximum transmission power ratio (explicit bounds are provided). We present first a downlink resource allocation scenario; the analysis is then extended to multihop networks. The policy is evaluated via simulations and is seen to perform very well even in the non-asymptotic regime. This policy is particularly suitable for sensor networks, which typically satisfy the asymptotic conditions required by our methodology.

The broadcast nature of wireless communication systems makes it vulnerable to eavesdroppping. To protect the system from eavesdropping, secrecy in communication systems is recently a very interesting topic. This presentation will address information theoretic approach for establishing secrecy in wiretap channels. Beginning with defining the wiretap channels and introducing information theoretic security, it will essentially provide theory and some important results starting from the seminal paper of Wyner up to secrecy in MIMO Gaussian wiretap channels.

This presentation will be introductory in nature. It will start with an introduction to the field of decentralized decision making, also known as distributed optimization. The theory behind it is useful in characterizing and modelling large and complicated networks with autonomous nodes that work towards a common goal. I will try to give a brief overview of the theory, models, applications and some important results in this field.

References: Problems in Decentralized Decision Making and Computation - J.N. Tsitsiklis Ph.D. Thesis, EECS, MIT, 1984; Consensus and Cooperation in Networked Multi-Agent Systems R Olfati-Saber, JA Fax, RM Murray - Proceedings of the IEEE, 2007.

A key element of mobile wireless networks is their distributed nature, which implies that often nodes only have a local view of the network. This leads to a situation where the ground truth for each node is different from other nodes. Yet, they have to make decisions about their transmission parameters like rate and power, such that their collective decision does not violate network capacity limits but still maximize spectral efficiency.

In this talk, we will first formulate a message-passing protocol which allows the information about the network to trickle via local message forwarding. The protocol naturally gives rise to networks where nodes have different amount of local information. We will then consider the performance of wireless systems with this local view. More precisely, we would quantify the information needed at nodes to come up with distributed strategies that match the sum capacity as the centralized strategy and the protocols associated to learn this knowledge.

Cognitive radio (CR) holds tremendous promise for increasing spectral efficiency in wireless communication systems. It spurred an explosion of interest for the past few years. Many key issues on CR have been well studied, such as efficient spectrum sensing and spectrum management schemes. However, there are still lots of questions and aspects to be tackled before CR can be seamlessly and opportunistically put into practice. Among them, one fundamental problem is that: what are the fundamental limits of communication in the presence of one or more cognitive radios in the network?

In this talk, I will present some existing results on fundamental limits on CR. First, the basic concepts and different paradigms of CR will be introduced. Then I will talk about some key issues for interweave and underlay CR paradigms. Next, existing results on the achievable rates and capacity regions of overlay CR channel will be mainly discussed. Through the whole talk, intuitive ideas and key coding techniques will be highlighted and compared to show how to explore the benefits of cognition and cooperation in wireless communication network.

We consider the Gaussian interference channel (GIFRC) with an intermediate relay. We first briefly review the known achievable schemes for relay channel and interference channel, and then we discuss the genie techniques when upperbounding the channel capacity. In particular, we study the "smart and useful" genie method. To find a good upperbound for the GIFRC, we consider the case when the relay is assumed to have abundant power and is named potent for that reason. By setting the power of the relay constraint to infinity, we observe that the capacity region is asymptotically equivalent to the case when the relay-destination links are noiseless and orthogonal to other links. The capacity region of the latter provides an outerbound for the GIFRC with finite relay power. We then show the sum capacity of the former can be upper bounded by a single-input-multiple-output interference channel with an antenna common to both receivers. We study both weak and strong interference cases. Both results, in turn, serve as upperbounds for the sum capacity of the GIFRC with finite relay power. Although our tight results are for when the relay has infinite power, numerical results show that with finite relay power, the performance is better than the cutset bound and our bounds are close to the known achievable sum rates for many scenarios of interest.

It is known that given the real sum of two independent uniformly distributed lattice points from the same nested lattice codebook, the eavesdropper can obtain at most 1 bit of information per channel regarding the value of one of the lattice points. In this work, we study the effect of this $1$ bit information on the equivocation expressed in three commonly used information theoretic measures, i.e., the Shannon entropy, the Renyi entropy and the min entropy. We then demonstrate its applications in an interference channel with a confidential message. In our previous work, we showed that nested lattice codes can outperform Gaussian codes for this channel when the achieved rate is measured with the weak secrecy notion. Here, with the Renyi entropy and the min entropy measure, we prove that the same secure degree of freedom is achievable with the 'strong' secrecy notion as well. A major benefit of the new coding scheme is that the strong secrecy is generated from a single lattice point instead of a sequence of lattice points. Hence the mutual information between the confidential message and the observation of the eavesdropper decreases much faster with the number of channel uses than previously known strong secrecy coding methods for nested lattice codes.

The ever-growing demand for wireless services has lead to relay assisted transmission schemes, where intermediate nodes serve as relays that may cooperate with source(s) or other relay(s) forming wireless ad hoc networks. Such ad hoc networks and important wireless applications such peer-to-peer systems are based on two-way traffic. As a result, there has been considerable attention in understanding and exploiting the bi-directional nature of the information flow with relay assistance. In this context, it is very typical that relay nodes forward a combination of previously received data received from different nodes, leading to the presence of side information at the end nodes. This phenomenon can be exploited by network coding, where data originating from different sources are mixed at intermediate nodes. Classical methods in characterizing limits on multiuser networks assume is that there is always data available to transmit at nodes, focusing on the physical layer. However, varying user demands and resulting traffic within different locations of wireless networks possess a stochastic nature, resulting to different levels of congestion in the network. This fact has lead to rising interest in cross-layer approaches in which physical layer decisions are made jointly with higher layers. In this conjunction, we focus on the impact of stochastic arrivals in the general setting where pairs of nodes exchange information via multiple intermediate relays. Throughout this work, we consider and address issues such as scheduling, rate allocation and stability regions for wireless networks based on relays.

We start by considering a pair of nodes with stochastic traffic flows who wish to communicate in a bi-directional communication scenario using intermediate relays in two-hop fashion. Intermediate relays are capable of XOR network coding and superposition coding. The presence of multiple relays results in beamforming gain. We first develop the throughput optimal control policy by tailoring the backpressure algorithm to the problem at hand. With multiple relays, whether relays will cooperate or one of the relays is selected for forwarding must be decided. Two main alternatives for network operation are either to have queues at the relays, i.e., hop-by-hop scheduling, or no queuing at the relays, i.e., immediate forwarding. In two-way networks with stochastic flows, we formulate the resulting stability regions using these two approaches. For the case of static channels, we show the stability regions of these two approaches are identical. On the other hand, for time-varying channels, we show that hop-by-hop scheduling outperforms immediate forwarding.

Next, we turn our emphasis in considering some other very critical issues in wireless networks such as minimizing consumption of resources and distributed operation. To that end, as a basic model, we consider a scenario in which two source nodes exchange stochastically varying traffic with the assistance of a bi-directional relay node that may perform network coding over the incoming packets. Each use of the relay incurs a unit cost, for example, representing the required transmission energy. This cost is shared between the source nodes when packets from both are transmitted via network coding; if traffic from a single source is sent, the cost is passed on to only that source. Our objective is to study transmission policies which trade-off the average cost with the average delay incurred at each source. We consider both centralized and decentralized algorithms. Different distributed algorithms operating with different knowledge of network parameters such as queue size within the network are proposed. The results illustrate new cost-delay trade-offs depending on different levels of cooperation and queue information availability in the network.

Wireless ad hoc networking is an emerging technology for next generation wireless communication systems due to its ability of providing communication without the need for infrastructure. In such networks, the system resources are limited: the terminals are constrained in energy, bandwidth, storage, and processing capabilities. As a result of the decentralized and possibly large scale network structure, resource management becomes a prominent design issue for wireless ad hoc networks. In this dissertation, we investigate resource management, with an emphasis on power, for various ad hoc networks including wireless sensor networks, parallel relay networks and multiuser two-way relay networks. We aim at providing efficient communication strategies that will fully utilize the limited resources to improve the Quality of Service (QoS) that ad hoc networks can offer.

We first study efficient scheduling for a delay-constrained wireless sensor network. We consider a two-tiered model of clustered sensors, whose data collection includes intra- and inter-cluster communications. We first find the optimum schedule with polynomial complexity for intra-cluster communications, which minimizes the total power of all sensors while maintaining a short term average throughput at each sensor.

Next, we show that the proposed scheduling protocol provides a near-optimum solution for inter-cluster communications where multi-antenna technique is employed. Next, we consider resource management for two types of relay-assisted ad hoc networks: parallel relay networks where the communication from a source to a destination is assisted by a number of intermediate relay nodes over orthogonal channels; multiuser two-way relay networks where multiple pairs of users exchange information with their pre-assigned partners via the help of a single relay node. Both relay networks in consideration are believed to be the building blocks of the future ad hoc networks.

For the parallel relay networks, we first propose a distributed decision mechanism for each relay to make decisions on whether to forward the source data. Next, we identify the optimum power allocation strategy, based on limited channel state information, that minimizes the total transmit power while providing a target signal-to-noise ratio (SNR) at the destination with an outage probability constraint. In addition, We consider two simpler distributed power allocation models, where the source does not contribute to the relay selection in the first one, and single relay is employed in the second one.

For the multiuser two-way relay networks, frequency/time/code division multiple access (F/T/CDMA) techniques can be employed to support multiuser communications. When F/TDMA is employed to provide orthogonal channels for each user pair, we investigate the optimum relay power allocation problem for various relay forwarding mechanisms to maximize the arbitrary weighted sum rate of all users. When CDMA is employed which results in an interference limited system, we design the multiuser two-way relaying scheme that allows each pair of partners share a common CDMA spreading signature, and solve the interference management problem by constructing the iterative power control and receiver updates that converge to the corresponding unique optimum.

Wireless communication system design must contend with several impairments in the wireless channel, such as time-varying channel gains, which makes it extremely challenging to provide performance guarantees for communication over these channels. Performance guarantees for delay-sensitive applications, in terms of data rate, delay and probability of violation, have traditionally been provided either through the pure (physical layer) channel coding approach, or through the pure (link layer) queuing approach.

The pure channel coding approach uses long codewords which span the entire allowable delay, to average over time-varying channel gains, and hence, guarantees low decoding error probability. However, this approach results in pessimistic performance guarantees, since it does not allow rate adaptation. On the other hand, the pure queuing approach allows rate adaptation, and hence, permits improved performance under a delay constraint. However, this approach results in overly optimistic performance guarantees, since it uses short codewords to allow rate adaptation across codewords, but ignores the decoding errors. In this talk, I will present a novel queued-code system design which combines ideas from channel coding and queuing approaches to overcome their individual limitations. The queued-code balances the requirements of the coding system and the queuing system to balance the errors in the two systems. A practical implementation of the queued-code based on low density parity check (LDPC) codes will also be presented.

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Chien-Jen Huang Chip McArtor

Title

Mikhail A. Lisovich

Semih Serbetli

Ender Tekin

Chien-Jen Huang Kyounghwan Lee

Min Chen

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Week 1

Joint Scheduling and Resource Allocation in CDMA Systems

Changyoon Oh

Week 2

Sandeep Bethanabhotla

Week 4

Girish Khandelwal

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Week 6

Semih Serbetli

Min Chen

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Week 1

Energy Efficient Transmission over a Wireless Link via Lazy Packet Scheduling

Changyoon Oh

Week 2

Design Guidelines for Wireless Sensor Networks: communication, clustering and aggregation

Sandeep Bethanabhotla

Week 3

A novel feedback scheme to increase throughput in multiple access radio systems

Girish Khandelwal

Week 5

Power optimal routing in wireless networks

Chien-Jen Huang

Week 6

Fading Relay Channels: Performance Limits and Space–Time Signal Design

Kyounghwan Lee