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Ahmed M. Alaa

Publications and source records attributed to Ahmed M. Alaa.

48 records · Page 3Linked to original sources

A Micro-foundation of Social Capital in Evolving Social Networks

A social network confers benefits and advantages on individuals (and on groups), the literature refers to these advantages as social capital. This paper presents a micro-founded mathematical model of the evolution of a social network and of the social capital of individuals within the network. The evolution of the network is influenced by the extent to which individuals are homophilic, structurally opportunistic, socially gregarious and by the distribution of types in the society. In the analysis, we identify different kinds of social capital: bonding capital, popularity capital, and bridging capital. Bonding capital is created by forming a circle of connections, homophily increases bonding capital because it makes this circle of connections more homogeneous. Popularity capital leads to preferential attachment: individuals who become popular tend to become more popular because others are more likely to link to them. Homophily creates asymmetries in the levels of popularity attained by different social groups, more gregarious types of agents are more likely to become popular. However, in homophilic societies, individuals who belong to less gregarious, less opportunistic, or major types are likely to be more central in the network and thus acquire a bridging capital.

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Evolution of Social Networks: A Microfounded Model

Many societies are organized in networks that are formed by people who meet and interact over time. In this paper, we present a first model to capture the micro-foundations of social networks evolution, where boundedly rational agents of different types join the network; meet other agents stochastically over time; and consequently decide to form social ties. A basic premise of our model is that in real-world networks, agents form links by reasoning about the benefits that agents they meet over time can bestow. We study the evolution of the emerging networks in terms of friendship and popularity acquisition given the following exogenous parameters: structural opportunism, type distribution, homophily, and social gregariousness. We show that the time needed for an agent to find "friends" is influenced by the exogenous parameters: agents who are more gregarious, more homophilic, less opportunistic, or belong to a type "minority" spend a longer time on average searching for friendships. Moreover, we show that preferential attachment is a consequence of an emerging doubly preferential meeting process: a process that guides agents of a certain type to meet more popular similar-type agents with a higher probability, thereby creating asymmetries in the popularity evolution of different types of agents.

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Self-organizing Networks of Information Gathering Cognitive Agents

In many scenarios, networks emerge endogenously as cognitive agents establish links in order to exchange information. Network formation has been widely studied in economics, but only on the basis of simplistic models that assume that the value of each additional piece of information is constant. In this paper we present a first model and associated analysis for network formation under the much more realistic assumption that the value of each additional piece of information depends on the type of that piece of information and on the information already possessed: information may be complementary or redundant. We model the formation of a network as a non-cooperative game in which the actions are the formation of links and the benefit of forming a link is the value of the information exchanged minus the cost of forming the link. We characterize the topologies of the networks emerging at a Nash equilibrium (NE) of this game and compare the efficiency of equilibrium networks with the efficiency of centrally designed networks. To quantify the impact of information redundancy and linking cost on social information loss, we provide estimates for the Price of Anarchy (PoA); to quantify the impact on individual information loss we introduce and provide estimates for a measure we call Maximum Information Loss (MIL). Finally, we consider the setting in which agents are not endowed with information, but must produce it. We show that the validity of the well-known "law of the few" depends on how information aggregates; in particular, the "law of the few" fails when information displays complementarities.

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Random Aerial Beamforming for Underlay Cognitive Radio with Exposed Secondary Users

In this paper, we introduce the exposed secondary users problem in underlay cognitive radio systems, where both the secondary-to-primary and primary-to-secondary channels have a Line-of-Sight (LoS) component. Based on a Rician model for the LoS channels, we show, analytically and numerically, that LoS interference hinders the achievable secondary user capacity when interference constraints are imposed at the primary user receiver. This is caused by the poor dynamic range of the interference channels fluctuations when a dominant LoS component exists. In order to improve the capacity of such system, we propose the usage of an Electronically Steerable Parasitic Array Radiator (ESPAR) antennas at the secondary terminals. An ESPAR antenna involves a single RF chain and has a reconfigurable radiation pattern that is controlled by assigning arbitrary weights to M orthonormal basis radiation patterns via altering a set of reactive loads. By viewing the orthonormal patterns as multiple virtual dumb antennas, we randomly vary their weights over time creating artificial channel fluctuations that can perfectly eliminate the undesired impact of LoS interference. This scheme is termed as Random Aerial Beamforming (RAB), and is well suited for compact and low cost mobile terminals as it uses a single RF chain. Moreover, we investigate the exposed secondary users problem in a multiuser setting, showing that LoS interference hinders multiuser interference diversity and affects the growth rate of the SU capacity as a function of the number of users. Using RAB, we show that LoS interference can actually be exploited to improve multiuser diversity via opportunistic nulling.

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Opportunistic Beamforming using Dumb Basis Patterns in Multiple Access Cognitive Channels

In this paper, we investigate multiuser diversity in interference-limited Multiple Access (MAC) underlay cognitive channels with Line-of-Sight interference (LoS) from the secondary to the primary network. It is shown that for $N$ secondary users, and assuming Rician interference channels, the secondary sum capacity scales like $\log\left(\frac{K^{2}+K}{\mathcal{W}\left(\frac{K e^{K}}{N}\right)}\right)$, where $K$ is the $K$-factor of the Rician channels, and $\mathcal{W}(.)$ is the Lambert W function. Thus, LoS interference hinders the achievable multiuser diversity gain experienced in Rayleigh channels, where the sum capacity grows like $\log(N)$. To overcome this problem, we propose the usage of single radio Electronically Steerable Parasitic Array Radiator (ESPAR) antennas at the secondary mobile terminals. Using ESPAR antennas, we induce artificial fluctuations in the interference channels to restore the $\log(N)$ growth rate by assigning random weights to orthogonal {\it basis patterns}. We term this technique as {\it Random Aerial Beamforming} (RAB). While LoS interference is originally a source of capacity hindrance, we show that using RAB, it can actually be exploited to improve multiuser interference diversity by boosting the {\it effective number of users} with minimal hardware complexity.

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On the Capacity of the Underwater Acoustic Channel with Dominant Noise Sources

This paper provides an upper-bound for the capacity of the underwater acoustic (UWA) channel with dominant noise sources and generalized fading environments. Previous works have shown that UWA channel noise statistics are not necessary Gaussian, especially in a shallow water environment which is dominated by impulsive noise sources. In this case, noise is best represented by the Generalized Gaussian (GG) noise model with a shaping parameter $β$. On the other hand, fading in the UWA channel is generally represented using an $α$-$μ$ distribution, which is a generalization of a wide range of well known fading distributions. We show that the Additive White Generalized Gaussian Noise (AWGGN) channel capacity is upper bounded by the AWGN capacity in addition to a constant gap of $\frac{1}{2} \log \left(\frac{β^{2} πe^{1-\frac{2}β} Γ(\frac{3}β)}{2(Γ(\frac{1}β))^{3}} \right)$ bits. The same gap also exists when characterizing the ergodic capacity of AWGGN channels with $α$-$μ$ fading compared to the faded AWGN channel capacity. We justify our results by revisiting the sphere-packing problem, which represents a geometric interpertation of the channel capacity. Moreover, UWA channel secrecy rates are characterized and the dependency of UWA channel secrecy on the shaping parameters of the legitimate and eavesdropper channels is highlighted.

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Opportunistic Spectrum Sharing using Dumb Basis Patterns: The Line-of-Sight Interference Scenario

We investigate a spectrum-sharing system with non-severely faded mutual interference links, where both the secondary-to-primary and primary-to-secondary channels have a Line-of-Sight (LoS) component. Based on a Rician model for the LoS channels, we show, analytically and numerically, that LoS interference hinders the achievable secondary user capacity. This is caused by the poor dynamic range of the interference channels fluctuations when a dominant LoS component exists. In order to improve the capacity of such system, we propose the usage of an Electronically Steerable Parasitic Array Radiator (ESPAR) antenna at the secondary terminals. An ESPAR antenna requires a single RF chain and has a reconfigurable radiation pattern that is controlled by assigning arbitrary weights to M orthonormal basis radiation patterns. By viewing these orthonormal patterns as multiple virtual dumb antennas, we randomly vary their weights over time creating artificial channel fluctuations that can perfectly eliminate the undesired impact of LoS interference. Because the proposed scheme uses a single RF chain, it is well suited for compact and low cost mobile terminals.

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Spectrum Sensing Via Reconfigurable Antennas: Fundamental Limits and Potential Gains

We propose a novel paradigm for spectrum sensing in cognitive radio networks that provides diversity and capacity benefits using a single antenna at the Secondary User (SU) receiver. The proposed scheme is based on a reconfigurable antenna: an antenna that is capable of altering its radiation characteristics by changing its geometric configuration. Each configuration is designated as an antenna mode or state and corresponds to a distinct channel realization. Based on an abstract model for the reconfigurable antenna, we tackle two different settings for the cognitive radio problem and present fundamental limits on the achievable diversity and throughput gains. First, we explore the (to cooperate or not to cooperate) tradeoff between the diversity and coding gains in conventional cooperative and noncooperative spectrum sensing schemes, showing that cooperation is not always beneficial. Based on this analysis, we propose two sensing schemes based on reconfigurable antennas that we term as state switching and state selection. It is shown that each of these schemes outperform both cooperative and non-cooperative spectrum sensing under a global energy constraint. Next, we study the (sensing-throughput) trade-off, and demonstrate that using reconfigurable antennas, the optimal sensing time is reduced allowing for a longer transmission time, and thus better throughput. Moreover, state selection can be applied to boost the capacity of SU transmission.

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Globally Optimal Cooperation in Dense Cognitive Radio Networks

The problem of calculating the local and global decision thresholds in hard decisions based cooperative spectrum sensing is well known for its mathematical intractability. Previous work relied on simple suboptimal counting rules for decision fusion in order to avoid the exhaustive numerical search required for obtaining the optimal thresholds. However, these simple rules are not globally optimal as they do not maximize the overall global detection probability by jointly selecting local and global thresholds. Instead, they maximize the detection probability for a specific global threshold. In this paper, a globally optimal decision fusion rule for Primary User signal detection based on the Neyman- Pearson (NP) criterion is derived. The algorithm is based on a novel representation for the global performance metrics in terms of the regularized incomplete beta function. Based on this mathematical representation, it is shown that the globally optimal NP hard decision fusion test can be put in the form of a conventional one dimensional convex optimization problem. A binary search for the global threshold can be applied yielding a complexity of O(log2(N)), where N represents the number of cooperating users. The logarithmic complexity is appreciated because we are concerned with dense networks, and thus N is expected to be large. The proposed optimal scheme outperforms conventional counting rules, such as the OR, AND, and MAJORITY rules. It is shown via simulations that, although the optimal rule tends to the simple OR rule when the number of cooperating secondary users is small, it offers significant SNR gain in dense cognitive radio networks with large number of cooperating users.

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Defeating the Eavesdropper: On the Achievable Secrecy Capacity using Reconfigurable Antennas

In this paper, we consider the transmission of confidential messages over slow fading wireless channels in the presence of an eavesdropper. We propose a transmission scheme that employs a single reconfigurable antenna at each of the legitimate partners, whereas the eavesdropper uses a single conventional antenna. A reconfigurable antenna can switch its propagation characteristics over time and thus it perceives different fading channels. It is shown that without channel side information (CSI) at the legitimate partners, the main channel can be transformed into an ergodic regime offering a \textit{secrecy capacity} gain for strict outage constraints. If the legitimate partners have partial or full channel side information (CSI), a sort of selection diversity can be applied boosting the maximum secret communication rate. In this case, fading acts as a friend not a foe.

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Band-Sweeping M-ary PSK (BS-M-PSK) Modulation and Transceiver Design

Channel Estimation is a major problem encountered by receiver designers for wireless communications systems. The fading channels encountered by the system are usually time variant for a mobile receiver. Besides, the frequency response of the channel is frequency selective for urban environments where the delay spread is quite large compared to the symbol duration. Estimating the channel is essential for equalizing the received data and removing the Inter-Symbol Interference (ISI) resulting from the dispersive channel. Hence, conventional transceivers insert pilot symbols of known values and detect the changes in it in order to deduce the channel response. Because these pilots carry no information, the throughput of the system is reduced. A Novel modulation scheme is presented in this work. The technique depends on using a carrier signal that has no fixed frequency, the carrier tone sweeps the band dedicated for transmission and detects the transfer function gain within the band. A carrier signal that is Frequency Modulated (FM) by a periodic ramp signal becomes Amplitude Modulated (AM) by the channel transfer function, and thus, the receiver obtains an estimate for the channel response without using pilots that decrease the systems throughput or data rate. The carrier signal itself acts as a dynamic frequency domain pilot. The technique only works for constant energy systems, and thus it is applied to PSK transceivers. Mathematical formulation, transceiver design and performance analysis of the proposed modulation technique are presented.

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Spectrum Sensing Via Reconfigurable Antennas: Is Cooperation of Secondary Users Indispensable?

This work presents an analytical framework for characterizing the performance of cooperative and noncooperative spectrum sensing schemes by figuring out the tradeoff between the achieved diversity and coding gains in each scheme. Based on this analysis, we try to answer the fundamental question: can we dispense with SUs cooperation and still achieve an arbitrary diversity gain? It is shown that this is indeed possible via a novel technique that can offer diversity gain for a single SU using a single antenna. The technique is based on the usage of a reconfigurable antenna that changes its propagation characteristics over time, thus creating an artificial temporal diversity. It is shown that the usage of reconfigurable antennas outperforms cooperative as well as non-cooperative schemes at low and high Signal-to-Noise Ratios (SNRs). Moreover, if the channel state information is available at the SU, an additional SNR gain can also be achieved.

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