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Robert Schober

Publications and source records attributed to Robert Schober.

At least 397 records · Page 22Linked to original sources

Comprehensive Reactive Receiver Modeling for Diffusive Molecular Communication Systems: Reversible Binding, Molecule Degradation, and Finite Number of Receptors

This paper studies the problem of receiver modeling in molecular communication systems. We consider the diffusive molecular communication channel between a transmitter nano-machine and a receiver nano-machine in a fluid environment. The information molecules released by the transmitter nano-machine into the environment can degrade in the channel via a first-order degradation reaction and those that reach the receiver nano-machine can participate in a reversible bimolecular reaction with receiver receptor proteins. Thereby, we distinguish between two scenarios. In the first scenario, we assume that the entire surface of the receiver is covered by receptor molecules. We derive a closed-form analytical expression for the expected received signal at the receiver, i.e., the expected number of activated receptors on the surface of the receiver. Then, in the second scenario, we consider the case where the number of receptor molecules is finite and the uniformly distributed receptor molecules cover the receiver surface only partially. We show that the expected received signal for this scenario can be accurately approximated by the expected received signal for the first scenario after appropriately modifying the forward reaction rate constant. The accuracy of the derived analytical results is verified by Brownian motion particle-based simulations of the considered environment, where we also show the impact of the effect of receptor occupancy on the derived analytical results.

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Capacity of the Two-Hop Relay Channel with Wireless Energy Transfer from Relay to Source and Energy Transmission Cost

In this paper, we investigate a communication system comprised of an energy harvesting (EH) source which harvests radio frequency (RF) energy from an out-of-band full-duplex relay node and exploits this energy to transmit data to a destination node via the relay node. We assume two scenarios for the battery of the EH source. In the first scenario, we assume that the EH source is not equipped with a battery and thereby cannot store energy. As a result, the RF energy harvested during one symbol interval can only be used in the following symbol interval. In the second scenario, we assume that the EH source is equipped with a battery having unlimited storage capacity in which it can store the harvested RF energy. As a result, the RF energy harvested during one symbol interval can be used in any of the following symbol intervals. For both system models, we derive the channel capacity subject to an average power constraint at the relay and an additional energy transmission cost at the EH source. We compare the derived capacities to the achievable rates of several benchmark schemes. Our results show that using the optimal input distributions at both the EH source and the relay is essential for high performance. Moreover, we demonstrate that neglecting the energy transmission cost at the source can result in a severe overestimation of the achievable performance.

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Joint Power and Subcarrier Allocation for Multicarrier Full-Duplex Systems

In this paper, we investigate resource allocation for multicarrier communication systems employing a full-duplex base station for serving multiple half-duplex downlink and uplink users simultaneously. We study the joint power and subcarrier allocation design for the maximization of the weighted sum throughput of the system. The algorithm design is formulated as a mixed combinatorial non-convex optimization problem and obtaining the globally optimal solution may require prohibitively high computational complexity. Therefore, a low computational complexity suboptimal iterative algorithm exploiting successive convex approximation is proposed to obtain a locally optimal solution. Simulation results confirm that the proposed suboptimal algorithm obtains a substantial improvement in system throughput compared to various existing baseline schemes.

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Channel Estimation for Diffusive Molecular Communications

In molecular communication (MC) systems, the \textit{expected} number of molecules observed at the receiver over time after the instantaneous release of molecules by the transmitter is referred to as the channel impulse response (CIR). Knowledge of the CIR is needed for the design of detection and equalization schemes. In this paper, we present a training-based CIR estimation framework for MC systems which aims at estimating the CIR based on the \textit{observed} number of molecules at the receiver due to emission of a \textit{sequence} of known numbers of molecules by the transmitter. Thereby, we distinguish two scenarios depending on whether or not statistical channel knowledge is available. In particular, we derive maximum likelihood (ML) and least sum of square errors (LSSE) estimators which do not require any knowledge of the channel statistics. For the case, when statistical channel knowledge is available, the corresponding maximum a posteriori (MAP) and linear minimum mean square error (LMMSE) estimators are provided. As performance bound, we derive the classical Cramer Rao (CR) lower bound, valid for any unbiased estimator, which does not exploit statistical channel knowledge, and the Bayesian CR lower bound, valid for any unbiased estimator, which exploits statistical channel knowledge. Finally, we propose optimal and suboptimal training sequence designs for the considered MC system. Simulation results confirm the analysis and compare the performance of the proposed estimation techniques with the respective CR lower bounds.

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Analysis and Design of Secure Massive MIMO Systems in the Presence of Hardware Impairments

To keep the hardware costs of future communications systems manageable, the use of low-cost hardware components is desirable. This is particularly true for the emerging massive multiple-input multiple-output (MIMO) systems which equip base stations (BSs) with a large number of antenna elements. However, low-cost transceiver designs will further accentuate the hardware impairments which are present in any practical communication system. In this paper, we investigate the impact of hardware impairments on the secrecy performance of downlink massive MIMO systems in the presence of a passive multiple-antenna eavesdropper. Thereby, for the BS and the legitimate users, the joint effects of multiplicative phase noise, additive distortion noise, and amplified receiver noise are taken into account, whereas the eavesdropper is assumed to employ ideal hardware. We derive a lower bound for the ergodic secrecy rate of a given user when matched filter (MF) data precoding and artificial noise (AN) transmission are employed at the BS. Based on the derived analytical expression, we investigate the impact of the various system parameters on the secrecy rate and optimize both the pilot sets used for uplink training and the AN precoding. Our analytical and simulation results reveal that 1) the additive distortion noise at the BS may be beneficial for the secrecy performance, especially if the power assigned for AN emission is not sufficient; 2) all other hardware impairments have a negative impact on the secrecy performance; 3) {\textcolor{blue}{despite their susceptibility to pilot interference in the presence of phase noise}}, so-called spatially orthogonal pilot sequences are preferable unless the phase noise is very strong; 4) the proposed generalized null-space (NS) AN precoding method can efficiently mitigate the negative effects of phase noise.

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Optimal Relay Selection for the Parallel Hybrid RF/FSO Relay Channel: Non-Buffer-Aided and Buffer-Aided Designs

Hybrid radio frequency (RF)/free space optical (FSO) systems are among the candidate enabling technologies for the next generation of wireless networks since they benefit from both the high data rates of the FSO subsystem and the high reliability of the RF subsystem. In this paper, we focus on the problem of throughput maximization in the parallel hybrid RF/FSO relay channel. In the parallel hybrid RF/FSO relay channel, a source node sends its data to a destination node with the help of multiple relay nodes. Thereby, for a given relay, the source-relay and the relay-destination FSO links are orthogonal with respect to each other due to the narrow beam employed for FSO transmission, whereas, due to the broadcast nature of the RF channel, half-duplex operation is required for the RF links if self-interference is to be avoided. Moreover, we consider the two cases where the relays are and are not equipped with buffers. For both cases, we derive the optimal relay selection policies for the RF and FSO links and the optimal time allocation policy for transmission and reception for the RF links. The proposed optimal protocols provide important insights for optimal system design. Since the optimal buffer-aided (BA) policy introduces an unbounded end-to-end delay, we also propose a suboptimal BA policy which ensures certain target average delays. Moreover, we present distributed implementations for both proposed optimal protocols. Simulation results demonstrate that a considerable gain can be achieved by the proposed adaptive protocols in comparison with benchmark schemes from the literature.

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Optimal Joint Power and Subcarrier Allocation for Full-Duplex Multicarrier Non-Orthogonal Multiple Access Systems

In this paper, we investigate resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems employing a full-duplex (FD) base station (BS) for serving multiple half-duplex (HD) downlink (DL) and uplink (UL) users simultaneously. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted sum system throughput. We apply monotonic optimization to develop an optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a system performance benchmark due to its high computational complexity. Furthermore, a suboptimal iterative scheme based on successive convex approximation is proposed to strike a balance between computational complexity and optimality. Our simulation results reveal that the proposed suboptimal algorithm achieves a close-to-optimal performance. Besides, FD MC-NOMA systems employing the proposed resource allocation algorithms provide a substantial system throughput improvement compared to conventional HD multicarrier orthogonal multiple access (MC-OMA) systems and other baseline schemes. Also, our results unveil that the proposed FD MC-NOMA systems achieve a fairer resource allocation compared to traditional HD MC-OMA systems.

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On the Outage Performance of Non-Orthogonal Multiple Access with One-Bit Feedback

In this paper, the outage performance of downlink non-orthogonal multiple access (NOMA) is investigated for the case where each user feeds back only one bit of its channel state information (CSI) to the base station. Conventionally, opportunistic one-bit feedback has been used in fading broadcast channels to select only one user for transmission. In contrast, the considered NOMA scheme adopts superposition coding to serve all users simultaneously in order to improve user fairness. A closed-form expression for the common outage probability (COP) is derived, along with the optimal diversity gains under two types of power constraints. Particularly, it is demonstrated that the diversity gain under a long-term power constraint is twice as large as that under a short-term power constraint. Furthermore, we study dynamic power allocation optimization for minimizing the COP, based on one-bit CSI feedback. This problem is challenging since the objective function is non-convex; however, under the short-term power constraint, we demonstrate that the original problem can be transformed into a set of convex problems. Under the long-term power constraint, an asymptotically optimal solution is obtained for high signal-to-noise ratio.

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Secure Massive MIMO Transmission with an Active Eavesdropper

In this paper, we investigate secure and reliable transmission strategies for multi-cell multi-user massive multiple-input multiple-output (MIMO) systems with a multi-antenna active eavesdropper. We consider a time-division duplex system where uplink training is required and an active eavesdropper can attack the training phase to cause pilot contamination at the transmitter. This forces the precoder used in the subsequent downlink transmission phase to implicitly beamform towards the eavesdropper, thus increasing its received signal power. Assuming matched filter precoding and artificial noise (AN) generation at the transmitter, we derive an asymptotic achievable secrecy rate when the number of transmit antennas approaches infinity. For the case of a single-antenna active eavesdropper, we obtain a closed-form expression for the optimal power allocation policy for the transmit signal and the AN, and find the minimum transmit power required to ensure reliable secure communication. Furthermore, we show that the transmit antenna correlation diversity of the intended users and the eavesdropper can be exploited in order to improve the secrecy rate. In fact, under certain orthogonality conditions of the channel covariance matrices, the secrecy rate loss introduced by the eavesdropper can be completely mitigated.

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Low-Complexity Hybrid Linear/Tomlinson-Harashima Precoding for Downlink Large-Scale MU-MIMO Systems

In this paper, we propose a novel low-complexity hybrid linear/Tomlinson-Harashima precoder (H-L-THP) for downlink large-scale multiuser multiple-input multiple-output (MU-MIMO) systems. The proposed precoder comprises an inner linear precoder which utilizes only the second order statistics of the channel state information (CSI) and outer THPs which use the instantaneous overall CSI of the cascade of the actual channel and the inner precoder. The user terminals are divided into groups, where for each group a THP successively mitigates the intra-group interference, whereas the inter-group interference is canceled by the inner linear precoder. Our simulation results show that the bit error rate (BER) of the proposed H-L-THP precoder is close to that of the conventional THP precoder, and is substantially lower than the BER of the commonly used regularized zero-forcing (RZF) precoder. Moreover, we derive exact expressions for the computational complexity of the proposed H-L-THP precoder in terms of the required numbers of floating-point operations. These results reveal that the proposed H-L-THP precoder has a much lower computational complexity than the conventional THP and RZF precoders, and is thus an excellent candidate for practical implementations.

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I/Q Imbalance Aware Widely-Linear Receiver for Uplink Multi-Cell Massive MIMO Systems

In-phase/quadrature-phase (I/Q) imbalance is one of the most important hardware impairments in communication systems. It arises in the analogue parts of direct conversion radio frequency (RF) transceivers and can cause severe performance losses. In this paper, I/Q imbalance (IQI) aware widely-linear (WL) channel estimation and data detection schemes for uplink multi-cell massive multiple-input multiple-output (MIMO) systems are proposed. The resulting receiver is a WL extension of the minimum mean square error (MMSE) receiver and jointly mitigates multi-user interference and IQI by processing the real and the imaginary parts of the received signal separately. The IQI arising at both the base station (BS) and the user terminals (UTs) is then taken into account. The considered channel state information (CSI) acquisition model includes the effects of both estimation errors and pilot contamination, which is caused by the reuse of the same training sequences in neighboring cells. We apply results from random matrix theory to derive analytical expressions for the achievable sum rates of the proposed IQI aware and conventional IQI unaware receivers. Our simulation results show that the performance of the proposed IQI aware WLMMSE receiver in a system with IQI is close to that of the MMSE receiver in an ideal system without IQI. Moreover, our results for the sum rate of the IQI unaware MMSE receiver reveal that the performance loss due to IQI can be large and, if left unattended, does not vanish for large numbers of BS antennas.

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A Bio-Synthetic Modulator Model for Diffusion-based Molecular Communications

In diffusion-based molecular communication (DMC), one important functionality of a transmitter nano-machine is signal modulation. In particular, the transmitter has to be able to control the release of signaling molecules for modulation of the information bits. An important class of control mechanisms in natural cells for releasing molecules is based on ion channels which are pore-forming proteins across the cell membrane whose opening and closing may be controlled by a gating parameter. In this paper, a modulator for DMC based on ion channels is proposed which controls the rate at which molecules are released from the transmitter by modulating a gating parameter signal. Exploiting the capabilities of the proposed modulator, an on-off keying modulation scheme is introduced and the corresponding average modulated signal, i.e., the average release rate of the molecules from the transmitter, is derived in the Laplace domain. By making a simplifying assumption, a closed-form expression for the average modulated signal in the time domain is obtained which constitutes an upper bound on the total number of released molecules regardless of this assumption. The derived average modulated signal is compared to results obtained with a particle based simulator. The numerical results show that the derived upper bound is tight if the number of ion channels distributed across the transmitter (cell) membrane is small.

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Robust Beamforming for SWIPT Systems with Non-linear Energy Harvesting Model

This paper investigates resource allocation for simultaneous wireless information and power transfer (SWIPT) downlink systems based on a non-linear energy harvesting model. The resource allocation algorithm design is formulated as a non-convex optimization problem for the maximization of the total harvested power. The proposed problem formulation not only takes into account imperfect channel state information (CSI) but also guarantees the quality-of-service (QoS) of information transfer. A novel iterative algorithm is proposed to obtain the globally optimal solution of the considered non-convex optimization problem. In each iteration, a rank-constrained semidefinite program (SDP) is solved optimally by SDP relaxation. Simulation results demonstrate the significant gains in harvested power and the robustness against CSI imperfection for the proposed optimal resource allocation, compared to a baseline scheme designed for perfect CSI and the conventional linear energy harvesting model.

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Optimal Joint Power and Subcarrier Allocation for MC-NOMA Systems

In this paper, we investigate the resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted system throughput. We employ monotonic optimization to develop the optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a performance benchmark due to its high complexity. Furthermore, to strike a balance between computational complexity and optimality, a suboptimal scheme with low computational complexity is proposed. Our simulation results reveal that the suboptimal algorithm achieves a close-to-optimal performance and MC-NOMA employing the proposed resource allocation algorithm provides a substantial system throughput improvement compared to conventional multicarrier orthogonal multiple access (MC-OMA).

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Physical Layer Security for Massive MIMO Systems Impaired by Phase Noise

In this paper, we investigate the impact of phase noise on the secrecy performance of downlink massive MIMO systems in the presence of a passive multiple-antenna eavesdropper. Thereby, for the base station (BS) and the legitimate users, the effect of multiplicative phase noise is taken into account, whereas the eavesdropper is assumed to employ ideal hardware. We derive a lower bound for the ergodic secrecy rate of a given user when matched filter data precoding and artificial noise transmission are employed at the BS. Based on the derived analytical expression, we investigate the impact of the various system parameters on the secrecy rate. Our analytical and simulation results reveal that distributively deployed local oscillators (LOs) can achieve a better performance than one common LO for all BS antennas as long as a sufficient amount of power is assigned for data transmission.

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I/Q-Imbalance Self-Interference Coordination

In this paper, we present a novel low-complexity scheme, which improves the performance of single-antenna multi-carrier communication systems, suffering from in-phase and quadrature (I/Q)-imbalance (IQI) at the receiver. We refer to the proposed scheme as I/Q-imbalance self-interference coordination (IQSC). IQSC does not only mitigate the detrimental effects of IQI, but, through appropriate signal processing, also coordinates the self-interference terms produced by IQI in order to achieve second-order frequency diversity. However, these benefits come at the expense of a reduction in transmission rate. More specifically, IQSC is a simple transmit diversity scheme that improves the signal quality at the receiver by elementary signal processing operations across symmetric (mirror) pairs of subcarriers. Thereby, the proposed transmission protocol has a similar complexity as Alamouti's space-time block coding scheme and does not require extra transmit power nor any feedback. To evaluate the performance of IQSC, we derive closed-form expressions for the resulting outage probability and symbol error rate. Interestingly, IQSC outperforms not only existing IQI compensation schemes but also the ideal system without IQI for the same spectral efficiency and practical target error rates, while it achieves almost the same performance as ideal (i.e., IQI-free) equal-rate repetition coding. Our findings reveal that IQSC is a promising low-complexity technique for significantly increasing the reliability of low-cost devices that suffer from high levels of IQI.

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Robust Resource Allocation for Full-Duplex Cognitive Radio Systems

In this paper, we investigate resource allocation algorithm design for full-duplex (FD) cognitive radio systems. The secondary network employs a FD base station for serving multiple half-duplex downlink and uplink users simultaneously. We study the resource allocation design for minimizing the maximum interference leakage to primary users while providing quality of service for secondary users. The imperfectness of the channel state information of the primary users is taken into account for robust resource allocation algorithm design. The algorithm design is formulated as a non-convex optimization problem and solved optimally by applying semidefinite programming (SDP) relaxation. Simulation results not only show the significant reduction in interference leakage compared to baseline schemes, but also confirm the robustness of the proposed algorithm.

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Low-Complexity MIMO Precoding with Discrete Signals and Statistical CSI

In this paper, we investigate the design of multiple-input multiple-output single-user precoders for finite-alphabet signals under the premise of statistical channel-state information at the transmitter. Based on an asymptotic expression for the mutual information of channels exhibiting antenna correlations, we propose a low-complexity iterative algorithm that radically reduces the computational load of existing approaches by orders of magnitude with only minimal losses in performance. The savings increase with the number of transmit antennas and with the cardinality of the signal alphabet, making it possible to supports values thereof that were unwieldy in existing solutions.

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