arXiv subjects

Björn Ottersten

Publications and source records attributed to Björn Ottersten.

At least 145 records · Page 8Linked to original sources

arXiv2016

Frequency of Arrival-based Interference Localization Using a Single Satellite

Intentional and unintentional interferences are an increasing threat for the satellite communications industry. In this paper, we aim to localize an interference with unknown location using frequency of arrival (FoA) technique by only relying on the measurements obtained through a single satellite. In each time instance, the satellite samples the interference and forwards it to the gateway to estimate its frequency. Since the satellite moves, each estimated frequency includes a Doppler shift, which is related to the location of the unknown interferer. The satellite's position, velocity, oscillator frequency, and the interference frequency are used at the gateway to build a location-related equation between the estimated frequency and the location of the unknown interference. Simultaneously with the interference signal, the satellite samples a reference signal to calibrate the estimated frequency and compensate for the mismatches between the available and real values of the satellite's position, velocity, and oscillator frequency. Multiple location-related equations obtained based on the FoA measurements, (at least two), along with the equation of the earth surface are used to localize the unknown interference. Simulations show that increasing the number of these equations, and the satellite velocity can improve the localization accuracy by 80% and 95%, respectively.

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arXiv2016

Directional Modulation via Symbol-Level Precoding: A Way to Enhance Security

Wireless communication provides a wide coverage at the cost of exposing information to unintended users. As an information-theoretic paradigm, secrecy rate derives bounds for secure transmission when the channel to the eavesdropper is known. However, such bounds are shown to be restrictive in practice and may require exploitation of specialized coding schemes. In this paper, we employ the concept of directional modulation and follow a signal processing approach to enhance the security of multi-user MIMO communication systems when a multi-antenna eavesdropper is present. Enhancing the security is accomplished by increasing the symbol error rate at the eavesdropper. Unlike the information-theoretic secrecy rate paradigm, we assume that the legitimate transmitter is not aware of its channel to the eavesdropper, which is a more realistic assumption. We examine the applicability of MIMO receiving algorithms at the eavesdropper. Using the channel knowledge and the intended symbols for the users, we design security enhancing symbol-level precoders for different transmitter and eavesdropper antenna configurations. We transform each design problem to a linearly constrained quadratic program and propose two solutions, namely the iterative algorithm and one based on non-negative least squares, at each scenario for a computationally-efficient modulation. Simulation results verify the analysis and show that the designed precoders outperform the benchmark scheme in terms of both power efficiency and security enhancement.

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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.

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arXiv2016

Secrecy Analysis on Network Coding in Bidirectional Multibeam Satellite Communications

Network coding is an efficient means to improve the spectrum efficiency of satellite communications. However, its resilience to eavesdropping attacks is not well understood. This paper studies the confidentiality issue in a bidirectional satellite network consisting of two mobile users who want to exchange message via a multibeam satellite using the XOR network coding protocol. We aim to maximize the sum secrecy rate by designing the optimal beamforming vector along with optimizing the return and forward link time allocation. The problem is non-convex, and we find its optimal solution using semidefinite programming together with a 1-D search. For comparison, we also solve the sum secrecy rate maximization problem for a conventional reference scheme without using network coding. Simulation results using realistic system parameters demonstrate that the bidirectional scheme using network coding provides considerably higher secrecy rate compared to that of the conventional scheme.

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arXiv2016

Joint Power Control in Wiretap Interference Channels

Interference in wireless networks degrades the signal quality at the terminals. However, it can potentially enhance the secrecy rate. This paper investigates the secrecy rate in a two-user interference network where one of the users, namely user 1, requires to establish a confidential connection. User 1 wants to prevent an unintended user of the network to decode its transmission. User 1 has to transmit such that its secrecy rate is maximized while the quality of service at the destination of the other user, user 2, is satisfied, and both user's power limits are taken into account. We consider two scenarios: 1) user 2 changes its power in favor of user 1, an altruistic scenario, 2) user 2 is selfish and only aims to maintain the minimum quality of service at its destination, an egoistic scenario. It is shown that there is a threshold for user 2's transmission power that only below or above which, depending on the channel qualities, user 1 can achieve a positive secrecy rate. Closed-form solutions are obtained in order to perform joint optimal power control. Further, a new metric called secrecy energy efficiency is introduced. We show that in general, the secrecy energy efficiency of user 1 in an interference channel scenario is higher than that of an interference-free channel.

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arXiv2016

Secure M-PSK Communication via Directional Modulation

In this work, a directional modulation-based technique is devised to enhance the security of a multi-antenna wireless communication system employing M-PSK modulation to convey information. The directional modulation method operates by steering the array beam in such a way that the phase of the received signal at the receiver matches that of the intended M-PSK symbol. Due to the difference between the channels of the legitimate receiver and the eavesdropper, the signals received by the eavesdropper generally encompass a phase component different than the actual symbols. As a result, the transceiver which employs directional modulation can impose a high symbol error rate on the eavesdropper without requiring to know the eavesdropper's channel. The optimal directional modulation beamformer is designed to minimize the consumed power subject to satisfying a specific resulting phase and minimal signal amplitude at each antenna of the legitimate receiver. The simulation results show that the directional modulation results in a much higher symbol error rate at the eavesdropper compared to the conventional benchmark scheme, i.e., zero-forcing precoding at the transmitter.

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arXiv2016

Sensing-Throughput Tradeoff for Interweave Cognitive Radio System: A Deployment-Centric Viewpoint

Secondary access to the licensed spectrum is viable only if interference is avoided at the primary system. In this regard, different paradigms have been conceptualized in the existing literature. Of these, Interweave Systems (ISs) that employ spectrum sensing have been widely investigated. Baseline models investigated in the literature characterize the performance of IS in terms of a sensing-throughput tradeoff, however, this characterization assumes the knowledge of the involved channels at the secondary transmitter, which is unavailable in practice. Motivated by this fact, we establish a novel approach that incorporates channel estimation in the system model, and consequently investigate the impact of imperfect channel estimation on the performance of the IS. More particularly, the variation induced in the detection probability affects the detector's performance at the secondary transmitter, which may result in severe interference at the primary users. In this view, we propose to employ average and outage constraints on the detection probability, in order to capture the performance of the IS. Our analysis reveals that with an appropriate choice of the estimation time determined by the proposed model, the degradation in performance of the IS can be effectively controlled, and subsequently the achievable secondary throughput can be significantly enhanced.

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arXiv2015

Distributed Coordinated Beamforming for Multi-cell Multigroup Multicast Systems

This paper considers coordinated multicast beamforming in a multi-cell wireless network. Each multiantenna base station (BS) serves multiple groups of single antenna users by generating a single beam with common data per group. The aim is to minimize the sum power of BSs while satisfying user-specific SINR targets. We propose centralized and distributed multicast beamforming algorithms for multi-cell multigroup systems. The NP-hard multicast problem is tackled by approximating it as a convex problem using the standard semidefinite relaxation method. The resulting semidefinite program (SDP) can be solved via centralized processing if global channel knowledge is available. To allow a distributed implementation, the primal decomposition method is used to turn the SDP into two optimization levels. The higher level is in charge of optimizing inter-cell interference while the lower level optimizes beamformers for given inter-cell interference constraints. The distributed algorithm requires local channel knowledge at each BS and scalar information exchange between BSs. If the solution has unit rank, it is optimal for the original problem. Otherwise, the Gaussian randomization method is used to find a feasible solution. The superiority of the proposed algorithms over conventional schemes is demonstrated via numerical evaluation.

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arXiv2015

Centralized Power Control in Cognitive Radio Networks Using Modulation and Coding Classification Feedback

In this paper, a centralized Power Control (PC) scheme and an interference channel learning method are jointly tackled to allow a Cognitive Radio Network (CRN) access to the frequency band of a Primary User (PU) operating based on an Adaptive Coding and Modulation (ACM) protocol. The learning process enabler is a cooperative Modulation and Coding Classification (MCC) technique which estimates the Modulation and Coding scheme (MCS) of the PU. Due to the lack of cooperation between the PU and the CRN, the CRN exploits this multilevel MCC sensing feedback as implicit channel state information (CSI) of the PU link in order to constantly monitor the impact of the aggregated interference it causes. In this paper, an algorithm is developed for maximizing the CRN throughput (the PC optimization objective) and simultaneously learning how to mitigate PU interference (the optimization problem constraint) by using only the MCC information. Ideal approaches for this problem setting with high convergence rate are the cutting plane methods (CPM). Here, we focus on the analytic center cutting plane method (ACCPM) and the center of gravity cutting plane method (CGCPM) whose effectiveness in the proposed simultaneous PC and interference channel learning algorithm is demonstrated through numerical simulations.

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arXiv2015

Performance Analysis of Underlay Cognitive Radio Systems: Estimation-Throughput Tradeoff

In this letter, we study the performance of cognitive Underlay Systems (USs) that employ power control mechanism at the Secondary Transmitter (ST). Existing baseline models considered for the performance analysis either assume the knowledge of involved channels at the ST or retrieve this information by means of a feedback channel, however, such situations hardly exist in practice. Motivated by this fact, we propose a novel approach that incorporates the estimation of the involved channels at the ST, in order to characterize the performance of USs under realistic scenarios. Moreover, we apply an outage constraint that captures the impact of imperfect channel knowledge, particularly on the interference power received at the primary receiver. Besides this, we employ a transmit power constraint at the ST to determine an operating regime for the US. Finally, we analyze an interesting tradeoff between the estimation time and the secondary throughput allowing an optimized performance of the US.

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arXiv2015

Precoding in Multibeam Satellite Communications: Present and Future Challenges

Whenever multibeam satellite systems target very aggressive frequency reuse in their coverage area, inter-beam interference becomes the major obstacle for increasing the overall system throughput. As a matter of fact, users located at the beam edges suffer from a very large interference for even a moderately aggressive planning of reuse-2. Although solutions for inter-beam interference management have been investigated at the satellite terminal, it turns out that the performance improvement does not justify the increased terminal complexity and cost. In this article, we pay attention to interference mitigation techniques that take place at the transmitter (i.e. the gateway). Based on this understanding, we provide our vision on advanced precoding techniques and user clustering methods for multibeam broadband fixed satellite communications. We also discuss practical challenges to deploy precoding schemes and the support introduced in the recently published DVB-S2X standard. Future challenges for novel configurations employing precoding are also provided.

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arXiv2015

Secrecy Energy Efficiency Optimization for MISO and SISO Communication Networks

Energy-efficiency, high data rates and secure communications are essential requirements of the future wireless networks. In this paper, optimizing the secrecy energy efficiency is considered. The optimal beamformer is designed for a MISO system with and without considering the minimum required secrecy rate. Further, the optimal power control in a SISO system is carried out using an efficient iterative method, and this is followed by analyzing the trade-off between the secrecy energy efficiency and the secrecy rate for both MISO and SISO systems.

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arXiv2015

Estimation-Throughput Tradeoff for Underlay Cognitive Radio Systems

Understanding the performance of cognitive radio systems is of great interest. To perform dynamic spectrum access, different paradigms are conceptualized in the literature. Of these, Underlay System (US) has caught much attention in the recent past. According to US, a power control mechanism is employed at the Secondary Transmitter (ST) to constrain the interference at the Primary Receiver (PR) below a certain threshold. However, it requires the knowledge of channel towards PR at the ST. This knowledge can be obtained by estimating the received power, assuming a beacon or a pilot channel transmission by the PR. This estimation is never perfect, hence the induced error may distort the true performance of the US. Motivated by this fact, we propose a novel model that captures the effect of channel estimation errors on the performance of the system. More specifically, we characterize the performance of the US in terms of the estimation-throughput tradeoff. Furthermore, we determine the maximum achievable throughput for the secondary link. Based on numerical analysis, it is shown that the conventional model overestimates the performance of the US.

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arXiv2014

Constructive Multiuser Interference in Symbol Level Precoding for the MISO Downlink Channel

This paper investigates the problem of interference among the simultaneous multiuser transmissions in the downlink of multiple antennas systems. Using symbol level precoding, a new approach towards the multiuser interference is discussed along this paper. The concept of exploiting the interference between the spatial multiuser transmissions by jointly utilizing the data information (DI) and channel state information (CSI), in order to design symbol-level precoders, is proposed. In this direction, the interference among the data streams is transformed under certain conditions to useful signal that can improve the signal to interference noise ratio (SINR) of the downlink transmissions. We propose a maximum ratio transmission (MRT) based algorithm that jointly exploits DI and CSI to glean the benefits from constructive multiuser interference. Subsequently, a relation between the constructive interference downlink transmission and physical layer multicasting is established. In this context, novel constructive interference precoding techniques that tackle the transmit power minimization (min power) with individual SINR constraints at each user's receivers is proposed. Furthermore, fairness through maximizing the weighted minimum SINR (max min SINR) of the users is addressed by finding the link between the min power and max min SINR problems. Moreover, heuristic precoding techniques are proposed to tackle the weighted sum rate problem. Finally, extensive numerical results show that the proposed schemes outperform other state of the art techniques.

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arXiv2014

Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users

In downlink multi-antenna systems with many users, the multiplexing gain is strictly limited by the number of transmit antennas $N$ and the use of these antennas. Assuming that the total number of receive antennas at the multi-antenna users is much larger than $N$, the maximal multiplexing gain can be achieved with many different transmission/reception strategies. For example, the excess number of receive antennas can be utilized to schedule users with effective channels that are near-orthogonal, for multi-stream multiplexing to users with well-conditioned channels, and/or to enable interference-aware receive combining. In this paper, we try to answer the question if the $N$ data streams should be divided among few users (many streams per user) or many users (few streams per user, enabling receive combining). Analytic results are derived to show how user selection, spatial correlation, heterogeneous user conditions, and imperfect channel acquisition (quantization or estimation errors) affect the performance when sending the maximal number of streams or one stream per scheduled user---the two extremes in data stream allocation. While contradicting observations on this topic have been reported in prior works, we show that selecting many users and allocating one stream per user (i.e., exploiting receive combining) is the best candidate under realistic conditions. This is explained by the provably stronger resilience towards spatial correlation and the larger benefit from multi-user diversity. This fundamental result has positive implications for the design of downlink systems as it reduces the hardware requirements at the user devices and simplifies the throughput optimization.

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arXiv2014

Capacity Limits and Multiplexing Gains of MIMO Channels with Transceiver Impairments

The capacity of ideal MIMO channels has a high-SNR slope that equals the minimum of the number of transmit and receive antennas. This letter analyzes if this result holds when there are distortions from physical transceiver impairments. We prove analytically that such physical MIMO channels have a finite upper capacity limit, for any channel distribution and SNR. The high-SNR slope thus collapses to zero. This appears discouraging, but we prove the encouraging result that the relative capacity gain of employing MIMO is at least as large as with ideal transceivers.

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arXiv2014

Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure

Transmit beamforming is a versatile technique for signal transmission from an array of $N$ antennas to one or multiple users [1]. In wireless communications, the goal is to increase the signal power at the intended user and reduce interference to non-intended users. A high signal power is achieved by transmitting the same data signal from all antennas, but with different amplitudes and phases, such that the signal components add coherently at the user. Low interference is accomplished by making the signal components add destructively at non-intended users. This corresponds mathematically to designing beamforming vectors (that describe the amplitudes and phases) to have large inner products with the vectors describing the intended channels and small inner products with non-intended user channels. While it is fairly easy to design a beamforming vector that maximizes the signal power at the intended user, it is difficult to strike a perfect balance between maximizing the signal power and minimizing the interference leakage. In fact, the optimization of multiuser transmit beamforming is generally a nondeterministic polynomial-time (NP) hard problem [2]. Nevertheless, this lecture shows that the optimal transmit beamforming has a simple structure with very intuitive properties and interpretations. This structure provides a theoretical foundation for practical low-complexity beamforming schemes. (See this lecture note for the complete abstract/introduction)

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arXiv2013

Beamforming for MISO Interference Channels with QoS and RF Energy Transfer

We consider a multiuser multiple-input single-output interference channel where the receivers are characterized by both quality-of-service (QoS) and radio-frequency (RF) energy harvesting (EH) constraints. We consider the power splitting RF-EH technique where each receiver divides the received signal into two parts a) for information decoding and b) for battery charging. The minimum required power that supports both the QoS and the RF-EH constraints is formulated as an optimization problem that incorporates the transmitted power and the beamforming design at each transmitter as well as the power splitting ratio at each receiver. We consider both the cases of fixed beamforming and when the beamforming design is incorporated into the optimization problem. For fixed beamforming we study three standard beamforming schemes, the zero-forcing (ZF), the regularized zero-forcing (RZF) and the maximum ratio transmission (MRT); a hybrid scheme, MRT-ZF, comprised of a linear combination of MRT and ZF beamforming is also examined. The optimal solution for ZF beamforming is derived in closed-form, while optimization algorithms based on second-order cone programming are developed for MRT, RZF and MRT-ZF beamforming to solve the problem. In addition, the joint-optimization of beamforming and power allocation is studied using semidefinite programming (SDP) with the aid of rank relaxation.

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