This paper presents an algorithm that exploits multipath propagation for the position estimation of mobile receivers. The proposed method utilizes two pieces of information of this multipath signal component: First the delay and thus the path length restricting possible reflection points to an ellipse. And second the Doppler shift of this multipath component to infer angular information along this ellipse. By exploiting relative Doppler information, obtained from the phase difference between the line-of-sight path and multipath components, the approach eliminates the need for strict synchronization requirements. In contrast to state-of-the-art methods that rely on the concept of static virtual transmitters and assume idealized straight wall geometries, the proposed algorithm directly estimates the positions of reflection points. The direct estimation of reflection points allows simultaneous localization and mapping of environments with arbitrary wall shapes. The feasibility of the approach is demonstrated through simulations incorporating delay and Doppler measurements of multipath components. Results confirm that the method enables accurate estimation of both receiver position and reflection points for a variety of wall geometries, including convex and concave surfaces.

Robotic swarms or portable sensor networks are emerging technologies for sensing physical processes that are spatially distributed- and temporally dynamic, both on Earth and in future Moon/Mars exploration missions. We develop a portable network composed of a multitude of self-organized “sensor eggs”. These eggs are equipped with ultra-wideband (UWB) transceivers, providing precise time and position information without additional infrastructures like Global Navigation Satellite Systems (GNSSs). Each egg is additionally equipped with environmental sensors, for example, a Sulfur dioxide gas sensor to explore volcanic activity. We use a real time decentralized particle filter (DPF) to estimate the a-posteriori probability density functions (PDFs) of the egg positions. These PDFs are then used in a static state binary Bayes filter for estimating the gas sources with potentially complex structures such as cracks on the volcano surface. The proposed sensor network is verified with an in-field experiment at La Fossa volcano on the island of Vulcano, Italy, in 2023.

A large number of missions to the Moon is planned in the coming years by both, public and private sectors. A high demand for a Lunar position, navigation and timing (PNT) system exists to aid landing, to support autonomous robotic exploration etc. ESA has proposed a satellite based system for communication and PNT. Furthermore, cooperative radio navigation for users on the Lunar surface, where PNT is provided through radio signals exchanged among robots and other entities, has been suggested. An analysis of the combination of satellite and cooperative navigation for Lunar PNT has not been done yet. In this paper, we provide a first estimation theoretic analysis of joint Lunar satellite and cooperative surface PNT. We derive the Bayesian Cramér-Rao bound (BCRB) and analyze the benefit of cooperation by comparing different cooperation strategies and scenarios, using system parameters from recent studies.

In recent years, the paradigm of navigation has shifted from pinpointing the location of a single agent to continuously estimating the full kinematic state of networked autonomous agents. In this paper, we propose a kinematics-aware information seeking algorithm for swarm navigation. The algorithm tightly couples state estimation and autonomous control given ranging and kinematic models. With the help of the Fisher information theory, agents generate information seeking command sequences. As an outcome, the swarm continuously optimizes its trajectory so that the agents’ position and orientation uncertainty is actively minimized. The proposed algorithm is verified by large-scale swarm simulations and demonstrated in a space-analogue mission of autonomous swarm navigation on the volcano Mount Etna.

Cooperative radio localization and navigation systems can be used in scenarios where the reception of global navigation satellite system (GNSS) signals is not possible or impaired. While the benefit of cooperation has been highlighted by many papers, calibration is not widely considered, but equally important in practice. Utilizing the signal propagation time requires group delay or ranging bias calibration and estimating the directions-of-arrival (DoAs) requires antenna response calibration. Often, calibration parameters are determined only once before operation. However, the calibration parameters are influenced by e.g. changing temperatures of radio frequency (RF) components or changing surroundings of antennas. To cope with that, we derive a cooperative simultaneous localization and calibration (SLAC) algorithm based on Bayesian filtering, which estimates antenna responses and ranging biases simultaneously with positions and orientations. By simulations, we show that the calibration parameters can be estimated during operation without additional sensors. We further proof practical applicability of SLAC by evaluating measurement data from robotic rovers. With SLAC, both ranging and DoAs estimation performance is improved, resulting in better position and orientation estimation accuracy. SLAC is thus able to provide reliable calibration and to mitigate model mismatch. Finally, we discuss open research questions and possible extensions of SLAC.

Autonomous robotic swarms have attracted increasing attention in recent years due to their enormous, principally unlimited, capability expansion from single robot systems. A communication system, as the `glue' in a swarm, plays an essential role that goes beyond conventional data exchange into localization, sensing, control, etc. Each building block of a swarm can be rooted from specific well-addressed research topic such as communications, signal processing, robotics, control, etc. However, an interdisciplinary view on swarm communication system, specially its impacts on other sub-systems, is still missing. In this paper, we share our experience in the assembling of a radio-based swarm system, from module design to system integration, from theoretical investigation to experimental platform development. With that we aim to shed light on some essential issues when designing a communication system particularly suitable for swarms.

Global navigation satellite systems (GNSSs) have become an essential part of maritime navigation, in particular for collision avoidance and vessel traffic management. The dependence on GNSSs creates vulnerability for maritime shipping. Driven by this vulnerability, the desire for a backup system for maritime navigation has been emerging. The VHF data exchange system (VDES) standard provides communication capabilities for maritime applications. VDES is currently being revised at the ITU-R Working Party 5B and foreseen to be finalized as early as 2022. As part of this revision, VDES will be extended by ranging and navigation functionalities, called R-Mode, as backup for maritime navigation. In this paper we evaluate the positioning performance of VDES R-Mode. For VDES R-mode performance evaluation, we derive estimation theory bounds for the distance and velocity estimation and introduce a Kalman filter which we use for position and velocity tracking. For validation of the positioning performance of VDES R-mode, we describe an experiment we conducted at Lake Ammer, southwest of Munich. Results obtained from this experiment show that VDES R-Mode achieves a positioning accuracy of 10 m, therefore providing an appropriate backup solution for maritime navigation.

A multitude of autonomous robotic platforms collectively organized as a swarm attracts increasing attention for remote sensing and exploration tasks. A navigation system is essential for the swarm to collectively localize itself as well as external sources. In this article, we propose a self-aware swarm navigation system that is conscious of the causality between its position and the localization uncertainty. This knowledge allows the swarm to move in a way to not only account for external mission objectives but also enhance position information. Position information for classical navigation systems has already been studied with the Fisher information (FI) and Bayesian information (BI) theories. We show how to extend these theories to a self-aware swarm navigation system, particularly emphasizing the collective performance. In this respect, fundamental limits and geometric interpretations of localization with generic observation models are discussed. We further propose a general concept of FI and BI based information seeking swarm control. The weighted position Cramér-Rao bound (CRB) and posterior CRB (PCRB) are employed flexibly as either a control cost function or constraints according to different mission criteria. As a result, the swarm actively adapts its position to enrich position information with different emerging collective behaviors. The proposed concept is illustrated by a case study of a swarm mission for gas exploration on Mars.

In multipath assisted positioning, multipath components (MPCs) are exploited for positioning as they are regarded as line-of-sight (LoS) signals from virtual transmitters. With simultaneous localization and mapping (SLAM), the locations of physical and virtual transmitters are estimated jointly with and relative to the user position. A robust data association scheme is crucial for the robustness of SLAM. In multipath assisted positioning, data association refers to the question which MPCs correspond to which transmitters. We say that a physical or virtual transmitter is visible to the user if the user is in LoS to the transmitter. Within this paper, we propose to map information on the visibility of physical and virtual transmitters in addition to their locations, and use such information for a reliable data association. Visibility information may stem from previous observations of a user, or from a visibility map of the scenario obtained from another user or a central entity. Our simulations in an indoor scenario show that information on the visibility of transmitters considerably improves the positioning performance by increasing the robustness of data association.

Non-stationary channel models play a crucial role in today's communication systems. Mobile-to-mobile channels are known to exhibit non-stationary behavior caused by the movement of transmitter and receiver. Non-stationarity can be addressed by introducing time-variant stochastic functions such as the time-variant instantaneous Doppler probability density function or time-variant instantaneous characteristic function. An algebraic analysis of the time-variant Doppler probability density function (pdf) in a classical Cartesian coordinate system is only numerically tractable due to trigonometric functions in the resulting expressions. In contrast, it has been shown that by using prolate spheroidal coordinates for 2D vehicle-to-vehicle channels the algebraic analysis becomes analytically tractable. In this paper, the analysis is extended to air-to-air channels. It is shown that the time-variant Doppler pdf can be represented without trigonometric functions. The description of the Doppler frequency in prolate spheroidal coordinates allows describing it as an algebraic curve. This permits the use of algebraic methods to analyze the Doppler frequency and derive the boundaries of the resulting Doppler pdf. Using the developed tools, we have investigated exemplary air-to-air scenarios. However, the methodology can be extended to any air-to-air configuration.

A huge variety of services require a precise localization. While global navigation satellite systems may show accurate positioning results in good view-to-sky conditions, their performance decreases drastically in case of shadowing and multipath propagation, such as indoors or in urban scenarios. Our approach is therefore to use terrestrial signals of opportunity for positioning. We exploit multipath propagation in a multipath-assisted positioning approach: each multipath component is regarded as being emitted by a virtual transmitter in a line-of-sight condition. Since the locations of the virtual transmitters are unknown, they are estimated in addition to the user position. This results in a simultaneous localization and mapping (SLAM) problem, where physical and virtual transmitters are considered as landmarks. This paper discusses our approach named Channel-SLAM, and extends it by a solution to the data association problem. We present and compare two different methods to decide for associations among virtual transmitters. By means of simulations, we show that data association can increase the positioning performance of Channel-SLAM remarkably.

In this paper, we investigate the performance of mobile vehicle positioning based on signal propagation delay estimation in the uplink case for a realistic propagation environment. In order to optimize the ranging performance, we introduce a parametric waveform. This waveform contains a scalar parameter for adjusting the distribution of the available signal power over the frequency. The optimization is achieved by a functional dependency between the waveform parameter and the positioning error. In order to derive a cost function, we combine the approaches of the Cramér-Rao and Ziv-Zakai bounds for position and propagation delay estimation. As an exemplary environment we consider a mobile vehicle located in an area surrounded by three base stations together with realistic propagation conditions provided by the WINNER II channel model. The results show that the waveform parameter has to be adjusted differently compared to a simple free space propagation scenario. Additionally, we compare the obtained results with a scenario with four base stations and a scenario where we use the WINNER II channel model in terms of line-of-sight received power and shadow fading to classify the effects of geometry and propagation conditions.

This paper describes an algorithm that exploits multipath propagation for position estimation of mobile receivers. We apply a novel algorithm based on recursive Bayesian filtering, named Channel-SLAM. This approach treats multipath components as signals emitted from virtual transmitters, which are time synchronized to the physical transmitter and static in their positions. Contrary to other approaches, Channel-SLAM considers also paths occurring due to multiple numbers of reflections or scattering as well as the combination. Hence, each received multipath component increases the number of transmitters resulting in a more accurate position estimate or enabling positioning when the number of physical transmitters is insufficient. Channel-SLAM estimates the receiver position and the positions of the virtual transmitters simultaneously; hence, the approach does not require any prior information, such as a room-layout or a database for fingerprinting. The only prior knowledge needed is the physical transmitter position as well as the initial receiver position and moving direction. Based on simulations, the position precision of Channel-SLAM is evaluated by a comparison to simplified algorithms and to the posterior Cramér-Rao lower bound. Furthermore, this paper shows the performance of Channel-SLAM based on measurements in an indoor scenario with only a single physical transmitter.

Cooperative positioning (CP) can be used either to calibrate the accumulated error from inertial navigation or as a stand-alone navigation system. Though intensive research has been conducted on CP, there is a need to further investigate the joint impact from the system level on the accuracy. We derive a posterior Cramér-Rao bound (PCRB) considering both the physical layer (PHY) signal structure and the asynchronous latency from the multiple access control layer (MAC). The PCRB shows an immediate relationship between the theoretical accuracy limit and the effective factors, e.g. geometry, node dynamic, latency, signal structure, power, etc. which is useful to assess a cooperative system. However, for a large-scale decentralized cooperation network, calculating the PCRB becomes difficult due to the high state dimension and the absence of global information. We propose an equivalent ranging variance (ERV) scheme which projects the neighbor's positioning uncertainty to the distance measurement inaccuracy. With this scheme, the interaction among the mobile terminals (MTs), e.g. measurement and communication can be decoupled. We use the ERV to derive a local PCRB (L-PCRB) which approximates the PCRB locally at each MT with low complexity. We further propose combining the ERV and L-PCRB together to improve the precision of the Bayesian localization algorithms. Simulation with an L-PCRB-aided distributed particle filter (DPF) in two typical cooperative positioning scenarios show a significant improvement comparing with the non-cooperative or standard DPF.

Ranging performance is a fundamental and crucial figure of merit for any position estimation technique. Cooperative positioning requires accurate range estimation with low latency. Common solutions employ time slots to sequentially range among all possible mobile nodes. In this case the number of ranging links increases quadratically with the number of users which increases latency significantly. We propose a subcarrier-interleaved round-trip delay ranging scheme with amplify and forward relaying to overcome this drawback. We show that we can reach linear complexity and significantly reduce latency. The obtained low latency allows higher flexibility and higher scalability compared to existing solutions. Furthermore, we study theoretical performances with derived Cramér-Rao lower-bounds for signals with orthogonal frequency division multiplex. Simulation results with 3GPP-LTE system parameters and our proposed sparse allocation show that our approach is well suited for low-latency and highly accurate range estimation.

Cellular communications systems suffer from interference in particular at cell edge regions. This is also the case for downlink synchronization signals. Such synchronization signals are base station specific and superimpose at a mobile terminal with different delays and amplitudes. This causes inter cellular interference depending on the cross correlation properties of the particular synchronization signals. Assuming knowledge about the positions of the serving and interfering base stations and having available a position estimate of the mobile terminal, there is a-priori information about the different signal propagation delays at the mobile terminal's position. Using this information, synchronization signals received from adjacent base stations can be timely related. For this reason, former interference can at least partly be turned into useful signal and exploited for improving synchronization performance especially at the critical cell edge regions. Within this paper we evaluate the benefit of position information for a mobile terminal in order to improve mobile terminal synchronization performance. The analysis is based on calculating the Cramér-Rao lower bound for this particular problem. In particular, we will derive additional Fisher information about OFDM symbol timing from position information about the mobile terminal.

This paper presents Cram'er-Rao Lower Bounds (CRLBs) for hybrid distance estimation algorithms, i.e., for received signal strength (RSS) and time of arrival (TOA) as well as for RSS and time difference of arrival (TDOA) measurements. The CRLBs are first evaluated with a simple channel model that consists of additive white Gaussian noise (AWGN), path loss (PL), and shadow fading (SF) in contrast to previous works. Several different CRLBs are dereived as the SF can be treated as nuisance parameter. Further, we apply the CRLBs to the WINNER II channel model and to current communication systems. Results show that the hybrid schemes always perform equal or better than RSS, TOA or TDOA only schemes, that the fourth type CRLB is the tightest bound, and that the distance when RSS performs better than TOA or TDOA increases with decreasing bandwidth.

Motivated by the possibility of decreasing the intersymbol interference (ISI) which is due to large delays of a multipath mobile radio channel, orthogonal frequency division multiplexing (OFDM) became very popular. However, the timevariance of the mobile radio channel induces intercarrier interference (ICI) yielding substantial channel estimation errors and thereby tremendous transmission impairments. Contrary to previous algorithms which resort to a linearization of the time-variant channel, we combat the ICI using eigenspaces of time-domain covariance matrices defined by the autocorrelation function of the Doppler spread. We perform a basis expansion using Slepian sequences and determine the basis coefficients of the time-variant channel by channel estimates from previous OFDM symbols. Once we know these basis coefficients, we obtain the necessary time-variant channel estimation by the Slepian sequences. These time-variant channel estimates allow a symbol detection in frequency domain which eliminates the ICI almost completely. Simulation results investigate both the signal to interference ratio (SIR) and the bit error ratio (BER) of our new ICI mitigation methods and reveal the superiority compared to previous algorithms for ICI reduction.

Time Based (TB) localization in terrestrial communications mobile radio as a complementation to global navigation satellite systems has gained recently plenty of interests. As an essential tool to develop suitable algorithms for joint communications and localizations in mobile radio networks, the wireless channel model has a growing significance. For both communications and localizations, the time evolution of multipath components is essential especially for tracking applications. Moreover, the Non Line-of-Sight (NLoS) error due to an undetectable line-of-sight path introduces an additional range error for TB localizations, which needs to be taken into account in the channel model. In this paper we present a space-alternating generalized expectation-maximization based Kalman filter method to efficiently estimate and track the time-variant multipath components based on a channel measurement campaign. The modeling of time-variant multipath characteristics, in terms of NLoS error, variance of path number, and the life span, are presented in this paper as well.

In this paper, location estimation algorithms for cellular communications systems employing orthogonal frequency division multiplexing (OFDM) are investigated. To determine the location of a mobile station, usually time difference of arrival (TDOA) measurements are performed with at least three base stations using pilot symbols included in the signal streams. With these TDOAs then the location is estimated. However, the timing estimation process is faced by different effects that restrict the performance. For instance, limited number of pilot symbols, inter-cell interference, and multipath propagation decrease the accuracy of the timing estimates, and hence, position estimates. Therefore, we propose to feed back decided data symbols where particularly data-aided timing estimation and interference cancellation are considered in the location estimation context. Simulation results for a 3GPP-LTE system show the ability of these algorithms to increase the overall accuracy and reliability of location estimates.

In this paper, we consider location estimation algorithms using cellular orthogonal frequency division multiplexing (OFDM) communications systems. In the classical approach the mobile station (MS) determines time difference of arrival (TDOA) information from the received signals of at least three base stations (BSs). With these TDOAs the location of the MS is estimated. However, only at the cell edge a good reception of several BSs is ensured. Especially for future systems targeting a frequency re-use of one, interference is a limiting factor. Hence, in the inner cell it is difficult to detect out-of-cell BSs with sufficient quality. Therefore, we propose an interference cancellation scheme to improve the performance in these critical situations for TDOA positioning. Simulation results for a 3GPP- LTE system show the ability of this approach to increase the accuracy and to extend the coverage of the overall location estimation.

The time based localization utilizing cellular communication networks has been investigated as a complementation to Global Navigation Satellite Systems (GNSS) for critical scenarios, like indoor or urban canyon areas. By suitable Hybrid Data Fusion (HDF) algorithms which combine the information from GNSS and terrestrial cellular networks, the estimated position accuracy can be improved. However, the wave propagation characteristics for joint GNSS and terrestrial mobile radio based localization as application has not been studied yet. Therefore, a measurement campaign for GNSS at 1.51 GHz and terrestrial radio at 5.2 GHz was performed. In this paper, an analysis of the outdoor to indoor channel for the joint localization as application is presented. It turns out to be that the Time of Arrival (ToA) bias, which is the difference between the geometric distance and the distance propagated by the first incoming wave, is depending on the elevation angle of incoming rays seen from the building to the transmitter. A comparison between two carrier frequencies is addressed.

Time Based (TB) localization in terrestrial cellular mobile radio as a complementation to Global Navigation Satellite Systems (GNSSs) has gained plenty of focuses. Due to absence of the Line-of Sight (LOS), Time of Arrival (ToA) of the First Path (FP) and/or corresponding Time Difference of Arrival (TDoA) are drifted from their true values. However, there are few analyses in terms of geolocations for current outdoor to indoor cellular channel models. In this paper ToA and TDoA error models based on the channel measurement are proposed, where both fit the Gaussian distribution well. Furthermore, with Monte Carlo simulation the positioning capabilities in a microcellular network scenario are investigated based on these models, where the TDoA based positioning promises a better solution compared to ToA.

The cell border area in a multi-carrier spread spectrum (MC-SS) based system is influenced by large inter-cell interference for a total frequency reuse in the neighboring cells. To handle this inter-cell interference and to enable reliable soft handoff procedures, macro diversity techniques can be applied for these scenarios. Applying multi-antenna transmit diversity techniques in a cellular environment, transmit diversity is transformed to macro diversity. In this paper, the cellular transmit diversity technique based on cyclic delay diversity (CDD), namely cellular CDD (C-CDD), is further investigated in terms of adaptive transmit powers and proper choices of the cyclic delays. The adaption of these system parameters results in a broadened receiving diversity area and eliminates the performance degradation within the standard C-CDD. Further, we show that the use of spread spectrum multi-carrier multiple access (SS-MC-MA) exploits the scarce system resources in a more efficient way with almost the same or better performance compared to the well-known multi-carrier code division multiple access (MC-CDMA) scheme.

We recall the principles of cyclic delay diversity (CDD) and discuss the properties and impact of this transmit antenna diversity technology. Different applications motivate variations of the CDD principle. This variants are briefly introduced and discussed. We show the application to several types of wireless systems, in particular terrestrial digital video broadcasting, cellular mobile radio communications systems and a wireless communications system using adaptive bit loading. Simulation results show the benefits of CDD for these kind of systems.

In this paper, we investigate delay diversity in Ricean fading channels implied by repeaters as a simple form of relay. We will outline the impact in broadcast and in mobile radio systems. Both systems investigate repeater or relaying as a gap filler to increase coverage. Repeaters have the advantage that existing systems will not be affected as there is no additional scheduling for the amply and forward unit needed. Without careful planning these gaps could be emphasized or new gaps could be created. Ray tracing tools take into account the actual SNR, but not the K factor of a Rice channel. Latter is a factor which could effect the coverage as relays are not necessarily beneficial.

Cyclic delay diversity (CDD) provides additional diversity in Rayleigh fading channels, and therefore, improves the system performance. For line-of-sight (LOS) propagation, e.g., the additive white Gaussian noise channel, the implementation of CDD yields to a performance loss. The power distribution among the transmit (TX) antenna branches is a further parameter which can freely be chosen for optimizing the system performance and allows to switch on/off CDD softly. The idea is to feed different power levels into the multiple TX antenna branches rather than distributing the TX power uniformly among the TX antennas. We exemplarily implement the soft CDD principle to the terrestrial digital video broadcasting system (DVB-T). We consider a Ricean multipath fading channel, which allows to control the ratio of LOS and non-LOS propagation power via the Ricean factor for simulations. Simulation results for 2-TX and 4-TX antenna CDD show that antenna power weighting significantly reduces the SNR loss in LOS propagation by the cost of a slight degradation of the SNR gain in non-LOS scenarios.

In this paper, we analyze the influence of the transmit antenna diversity techniques cyclic delay diversity (CDD) and discontinuous Doppler diversity (DDoD) on the channel observation at the receiver side for wireless communications systems based on orthogonal frequency division multiplexing (OFDM). These antenna diversity techniques influence the channel fading characteristic, and thus, are described as a modified channel. We analyze this modified channel in terms of its channel transfer function and fading correlation in time and frequency direction. We will see, that the fading correlation factorizes into an antenna related part and a propagation channel part. This is, the transmitter does not require any information about the channel itself in order to design roots in the correlation function. This analysis yields a guidance for the choice of the antenna configuration parameters, which is the goal of this paper. The proper choice of these parameters (cyclic delays, Doppler shifts) allows for reducing respectively removing fading correlation in time and/or frequency direction, and therefore, optimizing diversity gains.

The influence of time-varying cyclic delay diversity (TV-CDD) on the channel fading correlation properties is analyzed in this paper. TV-CDD is an attractive transmit diversity technique which increases not only the frequency diversity like pure CDD but also the time diversity in orthogonal frequency division multiplexing (OFDM) based systems. These transmit diversity schemes are characterized by no need of additional complexity at the receiver to exploit the increased transmit diversity. This paper gives first investigations regarding the resulting channel characteristics from TV-CDD and the impact on the system performance. Due to the increased frequency and time selectivity and a larger channel delay, an unintended higher channel estimation effort is possible. Therefore, we analyze the choice of the maximum cyclic delay. We show that the resulting channel for TV-CDD can be seen as an uncorrelated Rayleigh channel (except for the first sub-carrier) for a large maximum cyclic delay. Furthermore, analysis and simulation results demonstrate a feasible choice of small time-varying cyclic delays for guaranteeing the standard conformability of the TV- CDD technique at the receiver without significant performance degradations.

In this paper, we analyze an orthogonal frequency division multiplexing (OFDM) system employing combined space- time-frequency (STF) codes and an iterative receiver with extrinsic information transfer (EXIT) charts and bit-error rate plots. As STF codes, we examine orthogonal space-time block codes (OSTBCs), cyclic delay diversity, and discontinuous Doppler diversity. We present a combined STF code for eight transmit antennas with rate one. Another contribution of this work is the EXIT chart analysis demonstrating that EXIT charts are not always a suitable tool to analyze the performance of iterative receivers for STF coded OFDM systems. Further, error floors due to the mapping can be removed even for correlated channels by differential encoding and code doping the bits before the modulator.

In this paper, we address a new method called cellular cyclic delay diversity (C-CDD) to a cellular mobile radio communications system. A promising candidate for a next generation mobile downlink is multi-carrier code division multiple access (MC-CDMA). The C-CDD technique is exemplarily applied to MC-CDMA. The cyclic delay diversity technique increases the diversity in a system by cyclically shifted replicas of the transmitted signal over several transmit antennas. For improving the performance at the cell border in a cellular system, we introduce the cyclic delay diversity principle by sending replicas of the desired signal including a cyclic shift from adjacent base stations. The resulting C-CDD scheme is standard conformable. Therefore, no additional change in the mobile terminal is needed to exploit the C-CDD. The influence of the cyclic delay to a cellular MC-CDMA system is investigated. Furthermore, simulation results show the significant improvement of the performance at the cell border by using C-CDD in an MC-CDMA cellular system for different transmission scenarios.

In this paper, we present a synchronous code division multiplexing (CDM) scheme that uses orthogonal frequency division multiple access (OFDMA) to separate different users. The CDM component multiplies each data symbol with a different phase shift. This results in unique chips, which represent a new alphabet. The potential of this alphabet is shown by EXIT-charts. Therefore, the receiver can choose between an improved interference cancellation scheme as well as an iterative decoder. Latter does not rely on all chips of a spread sequence and increases the potential granularity of the CDM scheme

This paper investigates a downlink multiple-input multiple-output (MIMO) multi-carrier code division multiple access (MC-CDMA) system with iterative channel estimation (ICE) in the receiver. In MC-CDMA, each user's data symbols are spread with a Walsh-Hadamard code. Due to the superposition of different users' spread data signals, zero-valued subcarriers can occur, which cannot be used to compute least-squares (LS) estimates in ICE. For multiple transmit antennas, the data signals coincide non-orthogonal at each receive antenna. Hence, we propose two MIMO channel estimation methods to overcome these problems and avoid noise enhancement in ICE.

We address downlink systems based on orthogonal frequency division multiplexing (OFDM). The systems are situated in a sectorized cellular structure whereas the cellular environment model takes into account path loss and shadowing depending on the position of the mobile terminal. We investigate and compare the error performances in such environments of the OFDM based multiple access scheme (OFDMA) and the multi-carrier code division multiple access (MC-CDMA) scheme. The performance of an OFDMA system can be enhanced for a lower-loaded system by introducing a radio resource management (RRM). In this paper, we show that in the peripheral area of the desired sector OFDMA with an RRM can support the mobile terminal with a better error performance than MC-CDMA. In contrast, pure OFDMA cannot surpass the MC-CDMA error performance. For the inner part of the sector, MC-CDMA outperforms OFDMA for lower resource loads by utilizing its whole diversity of used sub-carriers.

Delay and Doppler spread of multipath fading channels have already been identified as sources of diversity in wireless communications systems. However, extensive delay- and Doppler spread may cause non-negligible intersymbol interference (ISI) and/or intercarrier interference (ICI) in OFDM systems. In this paper, we propose a method for increasing the Doppler spread of the multipath fading channel without causing additional ICI. The idea is to transmit the OFDM time domain signal predistorted via multiple transmit antennas. The proposed methods can be applied in addition to already existing OFDM systems without any modifications at the receiver, which makes them standards-compatible.

In this paper, we investigate a gradient based joint detection algorithm for MC-CDMA. The algorithm is based on the improvement of a suboptimum initial estimation, which itself can be obtained from an already known low complexity detection algorithm. For the improvement strategy, the algorithm calculates the gradient of the Euclidean distance function between the rebuilt initially estimated transmission signal and the received signal and goes into the direction of the steepest descent in order to find an improved estimation, which is closer to the received signal. Simulation results show, that for 4-QAM modulation and a spreading length of 8, an error performance close to maximum likelihood detection can be achieved with a complexity which is about 26 times lower.

In this paper, we investigate the applicability of the Plotkin code construction method to arbitrary finite sets, particularly complex valued modulation alphabets. Furthermore, we derive a recursive soft-in/soft-out decoding algorithm for these code constructions. The purpose is to have an encoding/decoding scheme available, which uses elements of finite sets-especially the complex valued elements of modulation alphabets-directly as information symbols. Simulations for some simple code constructions show the flexibility and performance of that codes and the proposed decoding algorithm.

In this paper the trade-off between time diversity and the inter-carrier interference (ICI) in an OFDM based MC-CDMA system is discussed. Our approach is to partially shift each spectrum of an OFDM symbol at the transmitter by using different phase shifts in the time domain at different antennas after the OFDM modulation. The summary signal at the receiver has a wider Doppler spectrum as the result of different uncorrelated Rayleigh fading channels. This leads to an artificially increased selective time channel transfer function, which is more favorable for the channel decoder at the receiver. The trade-off between Doppler diversity and ICI is found at about 9% maximum Doppler spread of the subcarrier distance for flat fading channels and frequency selective fading channel models. The distance to the independent Rayleigh channel bound by applying an MMSE detector is less than 2 dB for convolutional coding and about 2 dB for turbo coding at a BER of 10/sup -3/ for flat fading channels. For frequency selective fading channels this approaches to less than 1 dB to the independent Rayleigh channel bound.

We addresses channel estimation based on the discrete Fourier transform (DFT) applied to OFDM-based MIMO systems. By exploiting the properties of the DFT, channel estimation schemes for MIMO-OFDM system can be simplified. The Fourier transform translates phase shifts in the frequency domain to delays in the time domain. In order to exploit this feature, phase shifted pilot sequences are a perfect match to the Fourier transform in terms of separating the N/sub T/ superimposed signals, corresponding to N/sub T/ transmit antennas, without any further processing. The proposed estimator is shown to be optimum for the sample spaced channel, i.e. the channel tap delays are multiples of the sampling duration. A sub-optimum approximation for the non-sample spaced channel is also suggested.

We investigate broadband OFDM systems which apply beamforming in combination with different space-time diversity techniques. Various beamforming scenarios with transmitter and/or receiver sided beamforming are considered. Space-time diversity is obtained by cyclic delay diversity (CDD) in order to artificially shape the spectrum of the received signal. Thus, an advantageous distribution of the errors before a Viterbi channel decoder is obtained. Simulation results for the bit error rate performance are presented and compared for OFDM systems applying different beamforming scenarios and CDD in a Rayleigh fading channel. Maximum ratio combining (MRC) of the signals received on multiple beams/antennas is also taken into account in the performance analysis.

In this paper, we investigate different antenna diversity concepts, which can be easily applied to orthogonal frequency division multiplexing (OFDM) systems. The focus is to provide diversity schemes, which can be implemented to already existing OFDM systems without changing the standards. It is also possible to combine these techniques in a suitable manner. The introduced diversity techniques are applied to the DVB-T system for error performance investigations, which were done by simulation.