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Hamid Jafarkhani

Publications and source records attributed to Hamid Jafarkhani.

At least 73 records · Page 4Linked to original sources

Covert Wireless Communication with a Poisson Field of Interferers

In this paper, we study covert communication in wireless networks consisting of a transmitter, Alice, an intended receiver, Bob, a warden, Willie, and a Poisson field of interferers. Bob and Willie are subject to uncertain shot noise due to the ambient signals from interferers in the network. With the aid of stochastic geometry, we analyze the throughput of the covert communication between Alice and Bob subject to given requirements on the covertness against Willie and the reliability of decoding at Bob. We consider non-fading and fading channels. We analytically obtain interesting findings on the impacts of the density and the transmit power of the concurrent interferers on the covert throughput. That is, the density and the transmit power of the interferers have no impact on the covert throughput as long as the network stays in the interference-limited regime, for both the non-fading and the fading cases. When the interference is sufficiently small and comparable with the receiver noise, the covert throughput increases as the density or the transmit power of the concurrent interferers increases.

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Movement-efficient Sensor Deployment in Wireless Sensor Networks with Limited Communication Range

We study a mobile wireless sensor network (MWSN) consisting of multiple mobile sensors or robots. Three key factors in MWSNs, sensing quality, energy consumption, and connectivity, have attracted plenty of attention, but the interaction of these factors is not well studied. To take all the three factors into consideration, we model the sensor deployment problem as a constrained source coding problem. %, which can be applied to different coverage tasks, such as area coverage, target coverage, and barrier coverage. Our goal is to find an optimal sensor deployment (or relocation) to optimize the sensing quality with a limited communication range and a specific network lifetime constraint. We derive necessary conditions for the optimal sensor deployment in both homogeneous and heterogeneous MWSNs. According to our derivation, some sensors are idle in the optimal deployment of heterogeneous MWSNs. Using these necessary conditions, we design both centralized and distributed algorithms to provide a flexible and explicit trade-off between sensing uncertainty and network lifetime. The proposed algorithms are successfully extended to more applications, such as area coverage and target coverage, via properly selected density functions. Simulation results show that our algorithms outperform the existing relocation algorithms.

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Millimeter Wave Communications with Reconfigurable Antennas

The highly sparse nature of propagation channels and the restricted use of radio frequency (RF) chains at transceivers limit the performance of millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. Introducing reconfigurable antennas to mmWave can offer an additional degree of freedom on designing mmWave MIMO systems. This paper provides a theoretical framework for studying the mmWave MIMO with reconfigurable antennas. We present an architecture of reconfigurable mmWave MIMO with beamspace hybrid analog-digital beamformers and reconfigurable antennas at both the transmitter and the receiver. We show that employing reconfigurable antennas can provide throughput gain for the mmWave MIMO. We derive the expression for the average throughput gain of using reconfigurable antennas, and further simplify the expression by considering the case of large number of reconfiguration states. In addition, we propose a low-complexity algorithm for the reconfiguration state and beam selection, which achieves nearly the same throughput performance as the optimal selection of reconfiguration state and beams by exhaustive search.

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A New Reconfigurable Antenna MIMO Architecture for mmWave Communication

The large spectrum available in the millimeter-Wave (mmWave) band has emerged as a promising solution for meeting the huge capacity requirements of the 5th generation (5G) wireless networks. However, to fully harness the potential of mmWave communications, obstacles such as severe path loss, channel sparsity and hardware complexity should be overcome. In this paper, we introduce a generalized reconfigurable antenna multiple-input multiple-output (MIMO) architecture that takes advantage of lens-based reconfigurable antennas. The considered antennas can support multiple radiation patterns simultaneously by using a single RF chain. The degrees of freedom provided by the reconfigurable antennas are used to, first, combat channel sparsity in MIMO mmWave systems. Further, to suppress high path loss and shadowing at mmWave frequencies, we use a rate-one space-time block code. Our analysis and simulations show that the proposed reconfigurable MIMO architecture achieves full-diversity gain by using linear receivers and without requiring channel state information at the transmitter. Moreover, simulations show that the proposed architecture outperforms traditional MIMO transmission schemes in mmWave channel settings.

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On the Performance of MRC Receiver with Unknown Timing Mismatch-A Large Scale Analysis

There has been extensive research on large scale multi-user multiple-input multiple-output (MU-MIMO) systems recently. Researchers have shown that there are great opportunities in this area, however, there are many obstacles in the way to achieve full potential of using large number of receive antennas. One of the main issues, which will be investigated thoroughly in this paper, is timing asynchrony among signals of different users. Most of the works in the literature, assume that received signals are perfectly aligned which is not practical. We show that, neglecting the asynchrony can significantly degrade the performance of existing designs, particularly maximum ratio combining (MRC). We quantify the uplink achievable rates obtained by MRC receiver with perfect channel state information (CSI) and imperfect CSI while the system is impaired by unknown time delays among received signals. We then use these results to design new algorithms in order to alleviate the effects of timing mismatch. We also analyze the performance of introduced receiver design, which is called MRC-ZF, with perfect and imperfect CSI. For performing MRC-ZF, the only required information is the distribution of timing mismatch which circumvents the necessity of time delay acquisition or synchronization. To verify our analytical results, we present extensive simulation results which thoroughly investigate the performance of the traditional MRC receiver and the introduced MRC-ZF receiver.

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Asynchronous Channel Training in Multi-Cell Massive MIMO

Pilot contamination has been regarded as the main bottleneck in time division duplexing (TDD) multi-cell massive multiple-input multiple-output (MIMO) systems. The pilot contamination problem cannot be addressed with large-scale antenna arrays. We provide a novel asynchronous channel training scheme to obtain precise channel matrices without the cooperation of base stations. The scheme takes advantage of sampling diversity by inducing intentional timing mismatch. Then, the linear minimum mean square error (LMMSE) estimator and the zero-forcing (ZF) estimator are designed. Moreover, we derive the minimum square error (MSE) upper bound of the ZF estimator. In addition, we propose the equally-divided delay scheme which under certain conditions is the optimal solution to minimize the MSE of the ZF estimator employing the identity matrix as pilot matrix. We calculate the uplink achievable rate using maximum ratio combining (MRC) to compare asynchronous and synchronous channel training schemes. Finally, simulation results demonstrate that the asynchronous channel estimation scheme can greatly reduce the harmful effect of pilot contamination.

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Movement-efficient Sensor Deployment in Wireless Sensor Networks

We study a mobile wireless sensor network (MWSN) consisting of multiple mobile sensors or robots. Two key issues in MWSNs - energy consumption, which is dominated by sensor movement, and sensing coverage - have attracted plenty of attention, but the interaction of these issues is not well studied. To take both sensing coverage and movement energy consumption into consideration, we model the sensor deployment problem as a constrained source coding problem. %, which can be applied to different coverage tasks, such as area coverage, target coverage, and barrier coverage. Our goal is to find an optimal sensor deployment to maximize the sensing coverage with specific energy constraints. We derive necessary conditions to the optimal sensor deployment with (i) total energy constraint and (ii) network lifetime constraint. Using these necessary conditions, we design Lloyd-like algorithms to provide a trade-off between sensing coverage and energy consumption. Simulation results show that our algorithms outperform the existing relocation algorithms.

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Reconfigurable Antennas in mmWave MIMO Systems

The key obstacle to achieving the full potential of the millimeter wave (mmWave) band has been the poor propagation characteristics of wireless signals in this band. One approach to overcome this issue is to use antennas that can support higher gains while providing beam adaptability and diversity, i.e., reconfigurable antennas. In this article, we present a new architecture for mmWave multiple-input multiple-output (MIMO) communications that uses a new class of reconfigurable antennas. More specifically, the proposed lens-based antennas can support multiple radiation patterns while using a single radio frequency chain. Moreover, by using a beam selection network, each antenna beam can be steered in the desired direction. Further, using the proposed reconfigurable antenna in a MIMO architecture, we propose a new signal processing algorithm that uses the additional degrees of freedom provided by the antennas to overcome propagation issues at mmWave frequencies. Our simulation results show that the proposed reconfigurable antenna MIMO architecture significantly enhances the performance of mmWave communication systems.

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Energy Efficiency in Two-Tiered Wireless Sensor Networks

We study a two-tiered wireless sensor network (WSN) consisting of $N$ access points (APs) and $M$ base stations (BSs). The sensing data, which is distributed on the sensing field according to a density function $f$, is first transmitted to the APs and then forwarded to the BSs. Our goal is to find an optimal deployment of APs and BSs to minimize the average weighted total, or Lagrangian, of sensor and AP powers. For $M=1$, we show that the optimal deployment of APs is simply a linear transformation of the optimal $N$-level quantizer for density $f$, and the sole BS should be located at the geometric centroid of the sensing field. Also, for a one-dimensional network and uniform $f$, we determine the optimal deployment of APs and BSs for any $N$ and $M$. Moreover, to numerically optimize node deployment for general scenarios, we propose one- and two-tiered Lloyd algorithms and analyze their convergence properties. Simulation results show that, when compared to random deployment, our algorithms can save up to 79\% of the power on average.

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Downlink Non-Orthogonal Multiple Access with Limited Feedback

In this paper, we analyze downlink non-orthogonal multiple access (NOMA) networks with limited feedback. Our goal is to derive appropriate transmission rates for rate adaptation and minimize outage probability of minimum rate for the constant-rate data service, based on distributed channel feedback information from receivers. We propose an efficient quantizer with variable-length encoding that approaches the best performance of the case where perfect channel state information is available everywhere. We prove that in the typical application with two receivers, the losses in the minimum rate and outage probability decay at least exponentially with the minimum feedback rate. We analyze the diversity gain and provide a sufficient condition for the quantizer to achieve the maximum diversity order. For NOMA with $K$ receivers where $K > 2$, we solve the minimum rate maximization problem within an accuracy of $ε$ in time complexity of $O\left(K\log\frac{1}ε\right)$, then, we apply the previously proposed quantizers for $K = 2$ to the case of $K > 2$. Numerical simulations are presented to demonstrate the efficiency of our proposed quantizers and the accuracy of the analytical results.

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Interference Mitigation Using Asynchronous Transmission and Sampling Diversity

In this paper, we show that by investigating inherent time delays between different users in a multiuser scenario, we are able to cancel interference more efficiently. Time asynchrony provides another tool to cancel interference which results in preserving other resources like frequency, time and code. Therefore, we can save the invaluable resource of frequency band and also increase spectral efficiency. A sampling method is presented which results in independent noise samples and obviates the need for the complex process of noise whitening. By taking advantage of this sampling method and its unique structure, we implement maximum-likelihood sequence detection which outperforms synchronous maximum-likelihood detection. We also present successive interference cancellation with hard decision passing which gives rise to a novel forward-backward belief propagation method. Next, the performance of zero forcing detection is analyzed. Simulation results are also presented to verify our analysis.

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MDS Codes with Progressive Engagement Property for Cloud Storage Systems

Fast and efficient failure recovery is a new challenge for cloud storage systems with a large number of storage nodes. A pivotal recovery metric upon the failure of a storage node is repair bandwidth cost which refers to the amount of data that must be downloaded for regenerating the lost data. Since all the surviving nodes are not always accessible, we intend to introduce a class of maximum distance separable (MDS) codes that can be re-used when the number of selected nodes varies yet yields close to optimal repair bandwidth. Such codes provide flexibility in engaging more surviving nodes in favor of reducing the repair bandwidth without redesigning the code structure and changing the content of the existing nodes. We call this property of MDS codes progressive engagement. This name comes from the fact that if a failure occurs, it is shown that the best strategy is to incrementally engage the surviving nodes according to their accessing cost (delay, number of hops, traffic load or availability in general) until the repair-bandwidth or accessing cost constraints are met. We argue that the existing MDS codes fail to satisfy the progressive engagement property. We subsequently present a search algorithm to find a new set of codes named rotation codes that has both progressive engagement and MDS properties. Furthermore, we illustrate how the existing permutation codes can provide progressive engagement by modifying the original recovery scheme. Simulation results are presented to compare the repair bandwidth performance of such codes when the number of participating nodes varies as well as their speed of single failure recovery.

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Sensor Deployment with Limited Communication Range in Homogeneous and Heterogeneous Wireless Sensor Networks

We study the heterogeneous wireless sensor networks (WSNs) and propose the necessary condition of the optimal sensor deployment. Similar to that in homogeneous WSNs, the necessary condition implies that every sensor node location should coincide with the centroid of its own optimal sensing region. Moreover, we discuss the dynamic sensor deployment in both homogeneous and heterogeneous WSNs with limited communication range for the sensor nodes. The purpose of sensor deployment is to improve sensing performance, reflected by distortion and coverage. We model the sensor deployment problem as a source coding problem with distortion reflecting sensing accuracy. Traditionally, coverage is the area covered by the sensor nodes. However, when the communication range is limited, a WSN may be divided into several disconnected sub-graphs. Under such a scenario, neither the conventional distortion nor the coverage represents the sensing performance as the collected data in disconnected sub-graphs cannot be communicated with the access point. By defining an appropriate distortion measure, we propose a Restrained Lloyd (RL) algorithm and a Deterministic Annealing (DA) algorithm to optimize sensor deployment in both homogeneous and heterogeneous WSNs. Our simulation results show that both DA and RL algorithms outperform the existing Lloyd algorithm when communication range is limited.

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High-Rate Space Coding for Reconfigurable 2x2 Millimeter-Wave MIMO Systems

Millimeter-wave links are of a line-of-sight nature. Hence, multiple-input multiple-output (MIMO) systems operating in the millimeter-wave band may not achieve full spatial diversity or multiplexing. In this paper, we utilize reconfigurable antennas and the high antenna directivity in the millimeter-wave band to propose a rate-two space coding design for 2x2 MIMO systems. The proposed scheme can be decoded with a low complexity maximum-likelihood detector at the receiver and yet it can enhance the bit-error-rate performance of millimeter-wave systems compared to traditional spatial multiplexing schemes, such as the Vertical Bell Laboratories Layered Space-Time Architecture (VBLAST). Using numerical simulations, we demonstrate the efficiency of the proposed code and show its superiority compared to existing rate-two space-time block codes.

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High Rate/Low Complexity Space-Time Block Codes for 2x2 Reconfigurable MIMO Systems

In this paper, we propose a full-rate full-diversity space-time block code (STBC) for 2x2 reconfigurable multiple-input multiple-output (MIMO) systems that require a low complexity maximum likelihood (ML) detector. We consider a transmitter equipped with a linear antenna array where each antenna element can be independently configured to create a directive radiation pattern toward a selected direction. This property of transmit antennas allow us to increase the data rate of the system, while reducing the computational complexity of the receiver. The proposed STBC achieves a coding rate of two in a 2x2 MIMO system and can be decoded via an ML detector with a complexity of order M, where M is the cardinality of the transmitted symbol constellation. Our simulations demonstrate the efficiency of the proposed code compared to existing STBCs in the literature.

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Asynchronous Orthogonal Differential Decoding for Multiple Access Channels

We propose several differential decoding schemes for asynchronous multi-user MIMO systems based on orthogonal space-time block codes (OSTBCs) where neither the transmitters nor the receiver has knowledge of the channel. First, we derive novel low complexity differential decoders by performing interference cancelation in time and employing different decoding methods. The decoding complexity of these schemes grows linearly with the number of users. We then present additional differential decoding schemes that perform significantly better than our low complexity decoders and outperform the existing synchronous differential schemes but require higher decoding complexity compared to our low complexity decoders. The proposed schemes work for any square OSTBC, any constant amplitude constellation, any number of users, and any number of receive antennas. Furthermore, we analyze the diversity of the proposed schemes and derive conditions under which our schemes provide full diversity. For the cases of two and four transmit antennas, we provide examples of PSK constellations to achieve full diversity. Simulation results show that our differential schemes provide good performance. To the best of our knowledge, the proposed differential detection schemes are the first differential schemes for asynchronous multi-user systems.

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Differential Distributed Space-Time Coding with Imperfect Synchronization in Frequency-Selective Channels

Differential distributed space-time coding (D-DSTC) is a cooperative transmission technique that can improve diversity in wireless relay networks in the absence of channel information. Conventionally, it is assumed that channels are flat-fading and relays are perfectly synchronized at the symbol level. However, due to the delay spread in broadband systems and the distributed nature of relay networks, these assumptions may be violated. Hence, inter-symbol interference (ISI) may appear. This paper proposes a new differential encoding and decoding process for D-DSTC systems with multiple relays over slow frequency-selective fading channels with imperfect synchronization. The proposed method overcomes the ISI caused by frequency-selectivity and is robust against synchronization errors while not requiring any channel information at the relays and destination. Moreover, the maximum possible diversity with a decoding complexity similar to that of the conventional D-DSTC is attained. Simulation results are provided to show the performance of the proposed method in various scenarios.

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Differential Distributed Space-Time Coding with Imperfect Synchronization

Differential distributed space-time coding (D-DSTC) has been considered to improve both diversity and data-rate in cooperative communications in the absence of channel information. However, conventionally, it is assumed that relays are perfectly synchronized in the symbol level. In practice, this assumption is easily violated due to the distributed nature of the relay networks. This paper proposes a new differential encoding and decoding process for D-DSTC systems with two relays. The proposed method is robust against synchronization errors and does not require any channel information at the destination. Moreover, the maximum possible diversity and symbol-by-symbol decoding are attained. Simulation results are provided to show the performance of the proposed method for various synchronization errors and the fact that our algorithm is not sensitive to synchronization error.

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