arXiv subjects

Eduard Jorswieck

Publications and source records attributed to Eduard Jorswieck.

At least 73 records · Page 4Linked to original sources

arXiv2020

Beam-Domain Secret Key Generation for Multi-User Massive MIMO Networks

Physical-layer key generation (PKG) in multi-user massive MIMO networks faces great challenges due to the large length of pilots and the high dimension of channel matrix. To tackle these problems, we propose a novel massive MIMO key generation scheme with pilot reuse based on the beam domain channel model and derive close-form expression of secret key rate. Specifically, we present two algorithms, i.e., beam-domain based channel probing (BCP) algorithm and interference neutralization based multi-user beam allocation (IMBA) algorithm for the purpose of channel dimension reduction and multi-user pilot reuse, respectively. Numerical results verify that the proposed PKG scheme can achieve the secret key rate that approximates the perfect case, and significantly reduce the dimension of the channel estimation and pilot overhead.

cs.IT↗

arXiv2019

E2E Delay Guarantee for the Tactile Internet via joint NFV and Radio Resource Allocation

The Tactile Internet (TI) is one of the next generation wireless network services with end to end (E2E) delay as low as 1~ms. Since this ultra low E2E delay cannot be met in the current 4G network architecture, it is necessary to investigate this service in the next generation wireless network by considering new technologies such as network function virtualization (NFV). On the other hand, given the importance of E2E delay in the TI service, it is crucial to consider the delay of all parts of the network, including the radio access part and the NFV core part. In this paper, for the first time, we investigate the joint radio resource allocation (R-RA) and NFV resource allocation (NFV-RA) in a heterogeneous network where queuing delays, transmission delays, and delays resulting from virtual network function (VNF) execution are jointly considered. For this setup, we formulate a new resource allocation (RA) problem to minimize the total cost function subject to guaranteeing E2E delay of each user. Since the proposed optimization problem is highly non-convex, we exploit alternative search method (ASM), successive convex approximation (SCA), and heuristic algorithms to solve it. Simulation results reveal that in the proposed scheme can significantly reduce the network costs compared to the case where the two problems are optimized separately.

cs.NI↗

arXiv2019

Physical Layer Security in Multimode Fiber Optical Networks

Inverse precoding algorithms in multimode fiber based communication networks are used to exploit mode dependent losses on the physical layer. This provides an asymmetry between legitimate (Bob) and unlegitimate (Eve) receiver of messages resulting in a significant SNR advantage for Bob. In combination with dynamic mode channel changes, Eve has no chance to reconstruct a sent message even in a worst case scenario in which she is almighty. This is the first time, Physical Layer Security in a fiber optical network is investigated on the basis of measured transmission matrices. These results show that messages can be sent securely with conventional communication techniques. Translating the task of securing data from software to hardware represents the potential of a scientific paradigm shift. The introduced technique is a step towards the development of cyber physical systems.

cs.CR↗

arXiv2019

On Privacy Notions in Anonymous Communication

Many anonymous communication networks (ACNs) with different privacy goals have been developed. However, there are no accepted formal definitions of privacy and ACNs often define their goals and adversary models ad hoc. However, for the understanding and comparison of different flavors of privacy, a common foundation is needed. In this paper, we introduce an analysis framework for ACNs that captures the notions and assumptions known from different analysis frameworks. Therefore, we formalize privacy goals as notions and identify their building blocks. For any pair of notions we prove whether one is strictly stronger, and, if so, which. Hence, we are able to present a complete hierarchy. Further, we show how to add practical assumptions, e.g. regarding the protocol model or user corruption as options to our notions. This way, we capture the notions and assumptions of, to the best of our knowledge, all existing analytical frameworks for ACNs and are able to revise inconsistencies between them. Thus, our new framework builds a common ground and allows for sharper analysis, since new combinations of assumptions are possible and the relations between the notions are known.

cs.CR↗

arXiv2018

Energy Efficiency in Hybrid Beamforming Large-scale mmWave Multiuser MIMO with Spatial Modulation

The problem of radio resource allocation for global energy efficiency (GEE) maximization in mmWaves large-scale multiple-input multiple-output (MIMO) systems using hybrid-beamforming with spatial modulation is addressed. The theoretical properties of the optimization problem at hand are analyzed and two provably convergent optimization algorithms with affordable complexity are proposed. The former achieves the global optimum, while the latter trades off optimality with a lower computational complexity. Nevertheless, numerical results show that both algorithms attain global optimality in practical scenarios.

cs.IT↗

arXiv2018

Transceiver Design for GFDM with Index Modulation in Multi-user Networks

Index modulation (IM) techniques can be applied to the different media in order to achieve spectral- and energy-efficient communication as well as to the indices of the subcarriers of a generalized frequency division multiplexing (GFDM) data block. In this work, a novel transceiver architecture for multi-user GFDM-IM system is introduced. The performance of the GFDM-IM is studied by considering the bit error rate (BER) as performance metric. It is shown that better BER performance than the classical GFDM and the orthogonal frequency division multiplexing (OFDM) with IM can be achieved by employing IM to the GFDM.

cs.IT↗

arXiv2018

Distributed Energy Efficient Channel Allocation

Design of energy efficient protocols for modern wireless systems has become an important area of research. In this paper, we propose a distributed optimization algorithm for the channel assignment problem for multiple interfering transceiver pairs that cannot communicate with each other. We first modify the auction algorithm for maximal energy efficiency and show that the problem can be solved without explicit message passing using the carrier sense multiple access (CSMA) protocols. We then develop a novel scheme by converting the channel assignment problem into perfect matchings on bipartite graphs. The proposed scheme improves the energy efficiency and does not require any explicit message passing or a shared memory between the users. We derive bounds on the convergence rate and show that the proposed algorithm converges faster than the distributed auction algorithm and achieves near-optimal performance under Rayleigh fading channels. We also present an asymptotic performance analysis of the fast matching algorithm for energy efficient resource allocation and prove the optimality for large enough number of users and number of channels. Finally, we provide numerical assessments that confirm the energy efficiency gains compared to the state of the art.

cs.NI↗

arXiv2018

Uplink and Downlink Transceiver Design for OFDM with Index Modulation in Multi-user Networks

A new modulation scheme called OFDM with index modulation (OFDM-IM) is introduced recently. This scheme allows to transmit additional bits by mapping a part of incoming bit stream to the indices of the subcarriers. In this work, performance of OFDM-IM in multi-user networks for uplink and downlink scenario is studied. For both scenarios, novel base station designs are introduced in order to overcome the inter-user-interference (IUI). Simulation results show that OFDM-IM outperforms the classical OFDM in multi-user networks and IUI is eliminated successfully even in large networks.

cs.IT↗

arXiv2018

Performance of Media-based Modulation in Multi-user Networks

High spectral efficiency and low power consumption are the most challenging requirements of 5G networks since the number of devices are increased drastically. Media-based modulation (MBM) is a promising scheme in order to achieve these requirements. In this paper, the spectral efficiency of MBM scheme in single- and multi-user networks is studied. To find the spectral efficiency, information theoretical methods are used and tight lower- and upper-bounds are derived for the achievable rate. The performance of the system is studied for both correlated and uncorrelated constellation diagrams. It is shown that the entries of the constellation diagram for the sum rate region of multi-user case are always correlated. The characteristic of covariance matrix is derived and its impact on performance assessed.

cs.IT↗

arXiv2017

Hybrid Beamforming with Spatial Modulation in Multi-user Massive MIMO mmWave Networks

The cost of radio frequency (RF) chains is the biggest drawback of massive MIMO millimeter wave networks. By employing spatial modulation (SM), it is possible to implement lower number of RF chains than transmit antennas but still achieve high spectral efficiency. In this work, we propose a system model of the SM scheme together with hybrid beamforming at the transmitter and digital combining at the receiver. In the proposed model, spatially-modulated bits are mapped onto indices of antenna arrays. It is shown that the proposed model achieves approximately 5dB gain over classical multi-user SM scheme with only 8 transmit antennas at each antenna array. This gain can be improved further by increasing the number of transmit antennas at each array without increasing the number of RF chains.

cs.IT↗

arXiv2017

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

The characterization of the global maximum of energy efficiency (EE) problems in wireless networks is a challenging problem due to the non-convex nature of investigated problems in interference channels. The aim of this work is to develop a new and general framework to achieve globally optimal solutions. First, the hidden monotonic structure of the most common EE maximization problems is exploited jointly with fractional programming theory to obtain globally optimal solutions with exponential complexity in the number of network links. To overcome this issue, we also propose a framework to compute suboptimal power control strategies characterized by affordable complexity. This is achieved by merging fractional programming and sequential optimization. The proposed monotonic framework is used to shed light on the ultimate performance of wireless networks in terms of EE and also to benchmark the performance of the lower-complexity framework based on sequential programming. Numerical evidence is provided to show that the sequential fractional programming framework achieves global optimality in several practical communication scenarios.

math.OC↗

arXiv2017

Distributed Clustering for Multiuser Networks through Coalition Formation

Clustering mechanisms are essential in certain multiuser networks for achieving efficient resource utilization. This lecture note presents the theory of coalition formation as a useful tool for distributed clustering problems. We reveal the generality of the theory, and study complexity aspects which must be considered in multiuser networks.

cs.GT↗

arXiv2016

On the Capacity of an Elemental Two-Way Two-Tier Network

A basic setup of a two-tier network, where two mobile users exchange messages with a multi-antenna macrocell basestation, is studied from a rate perspective subject to beamforming and power constraints. The communication is facilitated by two femtocell basestations which act as relays as there is no direct link between the macrocell basestation and the mobile users. We propose a scheme based on physical-layer network coding and compute-and-forward combined with a novel approach that solves the problem of beamformer design and power allocation. We also show that the optimal beamformers are always a convex combination of the channels between the macro- and femtocell basestations. We then establish the cut-set bound of the setup to show that the presented scheme almost achieves the capacity of the setup numerically.

cs.IT↗

arXiv2016

Multi-Objective Signal Processing Optimization: The Way to Balance Conflicting Metrics in 5G Systems

The evolution of cellular networks is driven by the dream of ubiquitous wireless connectivity: Any data service is instantly accessible everywhere. With each generation of cellular networks, we have moved closer to this wireless dream; first by delivering wireless access to voice communications, then by providing wireless data services, and recently by delivering a WiFi-like experience with wide-area coverage and user mobility management. The support for high data rates has been the main objective in recent years, as seen from the academic focus on sum-rate optimization and the efforts from standardization bodies to meet the peak rate requirements specified in IMT-Advanced. In contrast, a variety of metrics/objectives are put forward in the technological preparations for 5G networks: higher peak rates, improved coverage with uniform user experience, higher reliability and lower latency, better energy efficiency, lower-cost user devices and services, better scalability with number of devices, etc. These multiple objectives are coupled, often in a conflicting manner such that improvements in one objective lead to degradation in the other objectives. Hence, the design of future networks calls for new optimization tools that properly handle the existence and tradeoffs between multiple objectives. In this article, we provide a review of multi-objective optimization (MOO), which is a mathematical framework to solve design problems with multiple conflicting objectives. (...) We provide a survey of the basic definitions, properties, and algorithmic tools in MOO. This reveals how signal processing algorithms are used to visualize the inherent conflicts between 5G performance objectives, thereby allowing the network designer to understand the possible operating points and how to balance the objectives in an efficient and satisfactory way. For clarity, we provide a case study on massive MIMO.

cs.IT↗

arXiv2015

Energy-Efficient Power Control: A Look at 5G Wireless Technologies

This work develops power control algorithms for energy efficiency (EE) maximization (measured in bit/Joule) in wireless networks. Unlike previous related works, minimum-rate constraints are imposed and the signal-to-interference-plus-noise ratio takes a more general expression, which allows one to encompass some of the most promising 5G candidate technologies. Both network-centric and user-centric EE maximizations are considered. In the network-centric scenario, the maximization of the global EE and the minimum EE of the network are performed. Unlike previous contributions, we develop centralized algorithms that are guaranteed to converge, with affordable computational complexity, to a Karush-Kuhn-Tucker point of the considered non-convex optimization problems. Moreover, closed-form feasibility conditions are derived. In the user-centric scenario, game theory is used to study the equilibria of the network and to derive convergent power control algorithms, which can be implemented in a fully decentralized fashion. Both scenarios above are studied under the assumption that single or multiple resource blocks are employed for data transmission. Numerical results assess the performance of the proposed solutions, analyzing the impact of minimum-rate constraints, and comparing the network-centric and user-centric approaches.

cs.IT↗

arXiv2014

Coalitional Games in MISO Interference Channels: Epsilon-Core and Coalition Structure Stable Set

The multiple-input single-output interference channel is considered. Each transmitter is assumed to know the channels between itself and all receivers perfectly and the receivers are assumed to treat interference as additive noise. In this setting, noncooperative transmission does not take into account the interference generated at other receivers which generally leads to inefficient performance of the links. To improve this situation, we study cooperation between the links using coalitional games. The players (links) in a coalition either perform zero forcing transmission or Wiener filter precoding to each other. The $ε$-core is a solution concept for coalitional games which takes into account the overhead required in coalition deviation. We provide necessary and sufficient conditions for the strong and weak $ε$-core of our coalitional game not to be empty with zero forcing transmission. Since, the $ε$-core only considers the possibility of joint cooperation of all links, we study coalitional games in partition form in which several distinct coalitions can form. We propose a polynomial time distributed coalition formation algorithm based on coalition merging and prove that its solution lies in the coalition structure stable set of our coalition formation game. Simulation results reveal the cooperation gains for different coalition formation complexities and deviation overhead models.

cs.IT↗

arXiv2013

Alternating Rate Profile Optimization in Single Stream MIMO Interference Channels

The multiple-input multiple-output interference channel is considered with perfect channel information at the transmitters and single-user decoding receivers. With all transmissions restricted to single stream beamforming, we consider the problem of finding all Pareto optimal rate-tuples in the achievable rate region. The problem is cast as a rate profile optimization problem. Due to its nonconvexity, we resort to an alternating approach: For fixed receivers, optimal transmission is known. For fixed transmitters, we show that optimal receive beamforming is a solution to an inverse field of values problem. We prove the solution's stationarity and compare it with existing approaches.

cs.IT↗

arXiv2012

Information Leakage Neutralization for the Multi-Antenna Non-Regenerative Relay-Assisted Multi-Carrier Interference Channel

In heterogeneous dense networks where spectrum is shared, users privacy remains one of the major challenges. On a multi-antenna relay-assisted multi-carrier interference channel, each user shares the frequency and spatial resources with all other users. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk on the frequency and spatial channels becomes information leakage. In this paper, we propose a novel secrecy rate enhancing relay strategy that utilizes both frequency and spatial resources, termed as information leakage neutralization. To this end, the relay matrix is chosen such that the effective channel from the transmitter to the colluding eavesdropper is equal to the negative of the effective channel over the relay to the colluding eavesdropper and thus the information leakage to zero. Interestingly, the optimal relay matrix in general is not block-diagonal which encourages users' encoding over the frequency channels. We proposed two information leakage neutralization strategies, namely efficient information leakage neutralization (EFFIN) and optimized information leakage neutralization (OPTIN). EFFIN provides a simple and efficient design of relay processing matrix and precoding matrices at the transmitters in the scenario of limited power and computational resources. OPTIN, despite its higher complexity, provides a better sum secrecy rate performance by optimizing the relay processing matrix and the precoding matrices jointly. The proposed methods are shown to improve the sum secrecy rates over several state-of-the-art baseline methods.

cs.IT↗