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We consider a Gaussian relay network, which has to protect the message from a powerful eavesdropper, which has the possibility of listening to the transmitted signals on orthogonal channels. The secrecy capacity of the Gaussian network is approximated by considering the corresponding network in the deterministic discrete superposition model. Upper and lower bounds on the secrecy capacity are found in terms of the deterministic model, which are potentially easier to evaluate. We perform this evaluation for the particular topology of the parallel relay network, where the relays form a parallel layer between the source and the destination. By analyzing the deterministic model, we approximate the secrecy capacity within a constant gap. The approximation can be expressed just in terms of the channel gains of the network. It is therefore possible to deduct that the simple scheme of hiding the transmitted signals in noise is approximately optimal., QC 20151028

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 transmitter's 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., QC 20140425

This paper characterizes achievable rate regions for the Gaussian partially cognitive interference channel with multiple cognitive pairs (K-PCIFC), where the cognitive transmitters know one part of the primary transmitter's message. We explore a novel methodology using the deterministic discrete superposition model (DSM). We find codes and their achievable rate regions in the DSM, and we show that they yield achievable rate regions in the Gaussian model. Our coding scheme in the DSM can be applied in general scenarios. We devise an achievable rate region for the K-PCIFC, which is within a constant gap to known outer bounds for K = 2 in the weak interference regime. From our expressions we derive guidelines for designing the cognitive link between the primary transmitter and the cognitive transmitters. Furthermore, we show that the gain from cognition diminishes for increasing K., QC 20140806

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 user. Both situations where the secondary transmitter is aware and unaware of the primary message are investigated and compared. Furthermore, we extend our results to the scenario where the secondary system comprises multiple users. For each case we sketch the derivation of the rates that are achievable from an information theoretic perspective. We then investigate the findings by numerical simulations. Our main result is that, in spite of the secrecy constraint, cooperation is beneficial in terms of the achievable rates. The secondary transmitter has the two contradicting tasks of helping the primary system and transmitting its own message. Our results show that both tasks can be accomplished simultaneously, improving both systems' performance. 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. In the case of multiple secondary users, the rate region reduces, which results in a lower individual rate. However, the linear increase in sumrate counterbalances this effect., QC 20121122

We consider the additive white Gaussian noise (AWGN) cognitive fading interference channel consisting of one primary and multiple secondary transmitter-receiver pairs. The secondary transmitters have non-causal knowledge of the primary message. We find a tuple of achievable rates by utilizing the discrete superposition model (DSM), which is a simplified, deterministic channel model. The coding scheme devised for the DSM can be translated into a coding scheme for the AWGN model, where the rate achieved in the AWGN model is at most a constant gap below the rate achieved in the DSM. We then calculate the average throughput of the secondary pairs under the assumption of Rayleigh fading channels. The main result is that our scheme performs well in the weak interference regime. The sum-throughput increases with the number of secondary pairs., QC 20121214

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 system's performance., QC 20121219

We find an achievable rate region for the partially cognitive interference channel in the weak interference regime, where the cognitive transmitter learns the primary message over a noiseless link with finite capacity. The rate region is established in the discrete superposition model, which has the property of approximating the AWGN model within a constant gap. In the high SNR regime our region is close to known outer bounds on the AWGN capacity region, yet its formulation is sufficiently simple to give valuable insights. Interestingly, the cognitive transmitter does not need to learn the complete primary message in order to achieve the rate region of the fully cognitive interference channel. The capacity of the noiseless link between the two transmitters is sufficiently large if it equals the single-user capacity of the cross-link from primary transmitter to secondary receiver., QC 20130115

The discrete superposition model (DSM) is intended to approximate the capacity region of AWGN networks. Finding the capacity region in the DSM is simpler due to its discrete and deterministic properties. For unicast in relay networks and for the multi-user interference channel it has been shown that the capacity regions of the DSM and of the AWGN model are within a constant gap. We extend this result to multiple unicast in networks consisting of broadcast and multiple-access channels by using a recent result on polymatroidal networks. We show that the capacity regions of the two models are within a constant additive gap and a constant multiplicative gap., QC 20130115

In this paper we show how the recently proposed linear finite-field deterministic model (LFFM) can be used to design transmission strategies for the corresponding AWGN model of wireless relay networks. The transmission scheme in the AWGN model uses hierarchical modulation to transmit information on multiple layers. We show that a transmission strategy in the LFFM can be translated to the AWGN model if it is coordinated, that is, if the amount of interference is limited in a certain way. We consider two types of coordination, full and partial, with different restrictions on the transmission scheme. In both cases we show that the rate in the AWGN model is at most a constant gap below the rate in the LFFM, which provides a link between the models. Closed-form upper bounds on the gap are derived based on the analysis of noise and interference forwarding. The bounds are evaluated numerically, and the dependency on the system parameters and the parameters of coordination are discussed. The trade-off between full and partial coordination and the corresponding parameters are illustrated., © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20130207

Recently, it has been shown that the capacity of certain Gaussian networks can be approximated by the capacity of the corresponding network in the discrete superposition model (DSM) [1], [2]. The gap between the capacities is an additive constant only depending on the number of nodes in the network. Hence, the capacity in the DSM is a good approximation in the high SNR regime. Finding this capacity involves optimizing over a finite set of coding strategies. However, the problem space grows with both the number of nodes and with SNR, rendering the optimization infeasible. In this paper we find upper and lower bounds on the capacity in the DSM. We start with the point-to-point channel, and we extend our strategy to the multiple-access channel. We show that the gap between our bounds is at most an additive constant independent of the channel gains. Hence, combining our results with the results of [1], [2], we find closed form bounds on the Gaussian capacity to within an additive constant., QC 20111114

We approximate the capacity of the Gaussian parallel relay network with general channel gains. Our strategy is to find capacity approximations for the corresponding network in the discrete superposition model and to use the fact that those are an approximation for the Gaussian capacity. The gap between our approximation and the Gaussian capacity is a constant depending only on the number of relays, hence it is a valuable characterization for the regime of high SNR and high rate., QC 20111114

In this paper we employ the recently proposed deterministic framework (Avestimehr et al.) to model and analyze cognitive networks. Despite its simplicity, this model captures fundamental aspects of networks and allows explicit calculation of the capacity of multicast relay networks. The performance results we obtain and the conclusions that we draw in the deterministic field can provide useful insights that can be applied on the analysis of Gaussian networks., © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.QC 20111117

A constant gap between the deterministic model of a class of a wireless relay network and its Gaussian model counterpart is derived. The method is constructive in the sense that a transmission solution in the deterministic model that obeys certain constraints can directly be translated into a transmission in the Gaussian model. We show that the rate in the Gaussian model is at most a constant gap below the rate in the deterministic model, and we derive an upper bound on this gap., QC 20110406

We analyze a multi-user MISO system employing zero-forcing precoding and user scheduling with an adjustable amount of fairness at the transmitter. The system shows a significant gain in sum-rate from multi-user diversity, even for a small number of users. Furthermore, a large fraction of this gain is attained even if the system is constraint to be as fair as the Round-Robin scheduler. The performance of the fair scheduler shows to be unaffected by partial channel state information at the transmitter in the slow fading regime., QC 20111114

We show how communication in the recently proposed deterministic finite field model can be translated into a transmission in the corresponding Gaussian model, using simple uncoded transmission. We find a lower bound on the number of received bits at each node as well as upper and lower bounds on the source-destination rate., QC 20110224