Frederic Gabry

Optimizing MDS Codes for Caching at the Edge

In this paper we investigate the problem of optimal MDS-encoded cache placement at the wireless edge to minimize the backhaul rate in heterogeneous networks. We derive the backhaul rate performance of any caching scheme based on file splitting and MDS encoding and we formulate the optimal caching scheme as a convex optimization problem. We then thoroughly investigate the performance of this optimal scheme for an important heterogeneous network scenario. We compare it to several other caching strategies and we analyze the influence of the system parameters, such as the popularity and size of the library files and the capabilities of the small-cell base stations, on the overall performance of our optimal caching strategy. Our results show that the careful placement of MDS-encoded content in caches at the wireless edge leads to a significant decrease of the load of the network backhaul and hence to a considerable performance enhancement of the network.

On the Optimization of the Secondary Transmitter's Strategy in Cognitive Radio Channels with Secrecy

This paper investigates cooperation for secrecy in cognitive radio networks. In particular, we consider a four-node cognitive scenario where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission. The cognitive transmitter can help the primary transmission, and it should also ensure that the primary message is not leaked to the secondary user. We consider two cognitive scenarios depending on whether the secondary transmitter knows the primary message or not. In the first case, the secondary transmitter is unaware of the primary transmitters message and acts as a helping interferer to enhance the secrecy of the primary transmission, whereas in the second case, relaying of the primary message is also within its capabilities. First, we find achievable rate regions for these two scenarios in the case of AWGN channels. We then investigate three different optimization problems: the maximization of the primary rate, the maximization of the secondary rate and the minimization of the secondary transmit power. For these optimization problems, we find closed-form expressions in important special cases. Furthermore, we analyze the cooperation between the primary and secondary transmitters from a game-theoretic perspective. We model their interaction as a Stackelberg game, for which we define and find the Stackelberg equilibrium. Finally, we use numerical examples to illustrate the rate regions, the three optimizations, and the impact of the Stackelberg game on the achievable rates and on the transmission strategies of the secondary transmitter.

Outage performances for amplify-and-forward, decode-and-forward and cooperative jamming strategies for the wiretap channel

In this paper, we investigate the wiretap channel in the presence of a cooperative relay node. We analyze and compare the outage performance of three cooperatives schemes: cooperative jamming (CJ), decode-and-forward (DF), and amplify-and-forward (AF) for the Rayleigh slow fading channel. In particular, we derive a closed-form expression for the outage probability for the DF and CJ strategies, which allows an optimal strategy selection in terms of outage performance. We compare the three cooperative schemes through numerical simulations.

Energy Efficiency Analysis of Cooperative Jamming in Cognitive Radio Networks With Secrecy Constraints

We investigate energy-efficient cooperation for secrecy in cognitive radio networks. In particular, we consider a four-node cognitive scenario where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission. The cognitive transmitter should ensure that the primary message is not leaked to the secondary user by using cooperative jamming. We investigate the optimal power allocation and power splitting at the secondary transmitter for our cognitive model to maximize the secondary energy efficiency (EE) under secrecy constraints. We formulate and analyze an important EE Stackelberg game between the two transmitters aiming at maximizing their utilities. We illustrate the analytical results through our geometrical model, highlighting the EE performance of the system and the impact of the Stackelberg game.

Cooperation for secure broadcasting in cognitive radio networks

This paper explores the trade-off between cooperation and secrecy in cognitive radio networks. We consider a scenario consisting of a primary and a secondary system. In the simplest case, each system is represented by a pair of transmitter and receiver. We assume a secrecy constraint on the transmission in the sense that the message of the primary transmitter has to be concealed from the secondary receiver. Both situations where the secondary transmitter is aware and unaware of the primary message are investigated and compared. In the first case, the secondary transmitter helps by allocating power for jamming, which increases the secrecy of the first message. In the latter case, it can also act as a relay for the primary message, thus improving the reliability of the primary transmission. Furthermore, we extend our results to the scenario where the secondary system comprises multiple receivers. For each case we present achievable rate regions. We then provide numerical illustrations for these rate regions. Our main result is that, in spite of the secrecy constraint, cooperation is beneficial in terms of the achievable rates. In particular, the secondary system can achieve a significant rate without decreasing the primary rate below the benchmark rate achievable without the help of the secondary transmitter. Finally, we investigate the influence of the distances between users on the systems performance.

On Energy-Efficient Edge Caching in Heterogeneous Networks

In this paper, we study the problem of content placement for caching at the wireless edge with the goal to maximize the energy efficiency (EE) of heterogeneous wireless networks. In particular, we consider the minimization of two fundamental metrics: the expected backhaul rate and the energy consumption. We derive both metrics in closed-form expressions, and we solve the minimization problem as a convex optimization for each, highlighting the existence of a tradeoff between the two metrics. Further, we show the advantage of encoding the data using maximum-distance separable (MDS) codes over the alternative concept of file fragmentation, with respect to both backhaul rate and energy consumption. Then, we thoroughly study the performance of the optimal MDS-encoded caching scheme in terms of overall energy consumption for an important heterogeneous network scenario. We compare our optimal strategy to several other sub-optimal caching strategies, including the caching scheme, minimizing the backhaul rate, and we analyze the effects of the system parameters on the overall performance. Our analysis can be generalized to any network topology and to any small-cell base station capability. Our results show that the optimal placement of MDS-encoded content in caches at the wireless edge increases significantly the overall EE of the heterogeneous network. This demonstrates the importance of the edge caching strategy for energy-efficient network designs.

Low-Complexity Scalable Iterative Algorithms for IEEE 802.11p Receivers

In this paper, we investigate receivers for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. Vehicular channels are characterized by multiple paths and time variations, which introduce challenges in the design of receivers. We propose an algorithm for IEEE 802.11p-compliant receivers, based on orthogonal frequency-division multiplexing (OFDM). We employ iterative structures in the receiver as a way to estimate the channel despite variations within a frame. The channel estimator is based on factor graphs (FGs), which allow the design of soft iterative receivers while keeping acceptable computational complexity. Throughout this paper, we focus on designing a receiver that offers a good complexity-performance tradeoff. Moreover, we propose a scalable algorithm to be able to tune the tradeoff, depending on the channel conditions. Our algorithm allows reliable communications while offering a considerable decrease in computational complexity. In particular, numerical results show the tradeoff between complexity and performance measured in computational time and bit error rate (BER), as well as frame error rate (FER) achieved by various interpolation lengths used by the estimator, which both outperform by decades the standard least squares (LS) solution. Furthermore, our adaptive algorithm shows a considerable improvement in terms of computational time and complexity against state-of-the-art and classical receptors while showing acceptable BER and FER performance.

On the Transmit Beamforming for MIMO Wiretap Channels: Large-System Analysis

With the growth of wireless networks, security has become a fundamental issue in wireless communications due to the broadcast nature of these networks. In this work, we consider MIMO wiretap channels in a fast fading environment, for which the overall performance is characterized by the ergodic MIMO secrecy rate. Unfortunately, the direct solution to finding ergodic secrecy rates is prohibitive due to the expectations in the rates expressions in this setting. To overcome this difficulty, we invoke the large-system assumption, which allows a deterministic approximation to the ergodic mutual information. Leveraging results from random matrix theory, we are able to characterize the achievable ergodic secrecy rates. Based on this characterization, we address the problem of covariance optimization at the transmitter. Our numerical results demonstrate a good match between the large-system approximation and the actual simulated secrecy rates, as well as some interesting features of the precoder optimization.

Clean relaying in cognitive radio networks with variational distance secrecy constraint

In this paper we investigate the cooperative secure communication in a four-node cognitive channel where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission with variational distance constraint. And the primary users secrecy rate is required to be unchanged. We propose the clean relaying with the cooperative jamming scheme to achieve this goal, where the secondary transmitter splits its transmitting phase into two non-overlapped intervals after successfully decoding the primary message. Due to the considered secrecy metric, we resort to the information spectrum method, to derive the achievable secrecy rates for the primary user. Then we formulate the secondary users rate maximization problem over the power allocation and time splitting at the cognitive transmitter under the constraint that primary users secrecy rate is unchanged. Numerical results show that the secondary transmitter can choose clean relaying or pure cooperative jamming according to the relative positions of the nodes to achieve better performance than the one without any clean phase.

Low-Complexity Puncturing and Shortening of Polar Codes

In this work, we address the low-complexity construction of shortened and punctured polar codes from a unified view. While several independent puncturing and shortening designs were attempted in the literature, our goal is a unique, low-complexity construction encompassing both techniques in order to achieve any code length and rate. We observe that our solution significantly reduces the construction complexity as compared to state-of-the-art solutions while providing a block error rate performance comparable to constructions that are highly optimized for specific lengths and rates. This makes the constructed polar codes highly suitable for practical application in future communication systems requiring a large set of polar codes with different lengths and rates.