In this work, the impact of the path delay differences in the various transmitter-receiver links on the channel capacity in an multiple-input multiple-output (MIMO) optical wireless communication (OWC) system with focus on line-of-sight (LOS) scenarios is investigated. Typically, the gain that can be achieved by using multiple transmit and receive elements in such a system is very limited, since the correlation between the different channels is extremely high. In the LOS channel, the magnitude of the transfer function is approximately constant for all frequencies. However, the different relative propagation times in the individual transmitter-receiver links lead to a varying frequency-dependent phase shift. So far, this aspect has been neglected in the most common optical free-space channel models, due to the relatively small path differences. In this paper, it is shown that even these small time delays have a significant impact on channel diversity for the highest modulation bandwidths reported in literature. With a single-sided modulation bandwidth of 1 GHz, the increase in normalized channel capacity due to the diversity caused by the different time delays is approximately 4 bps/Hz, depending on the geometry of the scenario. Therefore, accessing higher bandwidths not only increases the data throughput by shortening the symbol duration, but also enhances the potential gain from using MIMO techniques in a LOS OWC system.

In this paper, the reliability of spread Filter Bank Multicarrier (FBMC) Wireless Sensor Networks (WSNs) is analyzed for several off-tone jamming techniques to obtain a performance measure under intentional and unintentional interference. It is shown that FBMC is more robust against jamming signals with high Carrier Frequency Offset (CFO) than conventional Orthogonal Frequency Division Multiplexing (OFDM). Moreover, FBMC with Frequency Spreading (FS) shows a better performance than Multicarrier Code Division Multiple Access (MC-CDMA) when both are spread with a Walsh-Hadamard (W-H) code. When Time Spreading (TS) is applied, spread FBMC mostly outperforms MC-Direct Sequence (DS)-CDMA in terms of Bit Error Ratio (BER). A higher throughput can be also achieved when spread FBMC is implemented.

In this paper, a novel approach to detect and mitigate multi-tone interference (MTI) in a coded orthogonal frequency division multiplexing (OFDM) system based on deep neural networks (DNNs) is presented. The proposed approach utilizes the long short-term memory (LSTM) aiming to detect the indices of the jammed subcarriers within an OFDM symbol. Training data that is generated according to the statistical channel model is used for the offline training phase. The LSTMDNN is utilized as a classifier in the online deployment, where each subcarrier is classified as either jamming-free or jammed. The proposed approach based on LSTM-DNN requires no information about the interference characteristics. Simulation results show that the LSTM-DNN can learn and is able to classify the subcarriers with high accuracy compared to the traditional classification technique based on the energy detector (ED). In addition, simulation results demonstrate that the LSTMDNN is more robust to the variations in the wireless channel conditions compared to the ED classifier. As for the MTI mitigation technique, soft log-likelihood ratios (LLRs) weighting for the corresponding jammed subcarriers based on LSTM-DNN is proposed and compared with the traditional LLR erasing technique. Simulation comparison shows that the proposed LLR weighting can provide considerable performance enhancement.

In this paper, the performance of a Wireless Sensor and Actor Network (WSAN) based on the combination of Multicarrier Code Division Multiple Access (MC-CDMA) with Orthogonal Frequency Division Multiplexing (OFDM) and Offset Quadrature Amplitude Modulation (OQAM)-OFDM using the PHYDYAS prototype filter is investigated and compared under Barrage Noise Jamming (BNJ), Partial Band Jamming (PBJ), and Multi-tone Jamming (MTJ). Different spreading methods were applied to both transmission techniques. Under a Line-Of-Sight (LOS) indoor industrial channel with Additive White Gaussian Noise (AWGN), it is proven that CDMA-OQAM-OFDM variants outperform CDMA-OFDM in terms of Bit Error Ratio (BER) unless they use Time Spreading (TS) under the influence of MTJ.

Performance evaluations for heterogeneous communication technologies in the area of V2X safety applications for either improvement, comparison or combination purposes are in general focusing on the realistic representation of the upper communication stack layers, but therefore - often for the sake of simplicity - reducing the radio propagation channel to a maximum range model. The impact and hence the importance to model the environment dependent propagation effects in a representative manner has already been stressed in the literature several times - but separately for ad-hoc or cellular systems and not under the consideration of V2X safety-beaconing applications. By combining a realistic heterogeneous radio propagation channel model with a state-of-the-art V2X communication stack, a representative performance comparison of safety-relevant beaconing applications for 802.11p single-hop broadcast (SHB) and LTE Geocast can be conducted. Our simulation results show that the effects caused by the radio propagation channel cannot be neglected as they significantly impact key communication performance metrics such as channel gain, packet error ratio (PER) and channel load, where we primarily focus on the latter one to give further research directions for an efficient dissemination of safety-relevant V2X beacons.

The need for secured communication between computationally weak wireless devices has driven the development of novel key generation protocols. Various schemes for extracting symmetric cryptographic keys out of wireless channel properties have been proposed during recent years, making the generation protocol more and more efficient for individual applications. However, often these schemes were evaluated based on theoretical models and without considering practical effects. We present a system for PHY-based key generation with two legitimate users as well as a passive attacker of equivalent power and analyze results from practical measurements in real world scenarios. Furthermore we extend practical constraints by considering heterogeneous setups and show the impact onto representative performance indicators.

The generation of symmetric cryptographic keys based on reciprocal channel properties has evolved as a promising approach in recent years, especially for devices with only little computational power. Different schemes individually addressing constraints from special setups have been proposed, but most schemes generally suffer from bad performance in case of (nearly) static scenarios. Addressing this dilemma, we present a novel approach for physical layer based key generation with two static users supported by a third party. In contrast to other solutions, this approach does not rely on special hardware like multiple antennas and does not let the third party know anything about the secret key, as the helper is potentially not fully trusted. The scheme does not evade to other diversity domains, but still exploits temporal and spatial diversity. We present thorough performance and security analysis, also taking a passive attacker into account.

The IEEE 802.15.4 standard uses carrier sense multiple access with collision avoidance (CSMA/CA) algorithm as the medium access mechanism, which employs a binary exponential backoff (BEB) mechanism to control the access of nodes to the wireless medium. However, CSMA/CA algorithm does not support network self-adaptivity and differentiated services. We address these problems by proposing an adaptive priority-based service-differentiation CSMA/CA algorithm (APB-CSMA/CA) for differentiated services for IEEE 802.15.4. The proposed algorithm includes two mechanisms, 1) adaptive backoff mechanism. The nodes can dynamically adjust the backoff period according to the actual status of current network. 2) priority-based service-differentiation mechanism. In this mechanism, different parameters are given to different classes of services to provide multi-levels differentiated services. In addition, a theoretical analysis based on Markov chain is proposed to derive a mathematical model for our proposal. Both analytical and simulation results show that the proposed algorithm performs better than IEEE 802.15.4, which significantly improves reliability and channel utilization.

In this paper, we focus on a shared relay architecture in the cellular network instead of deploying multiple separated relays near cell edges. The advantage of shared relaying is the joint processing of signals at the relay to suppress the inter-cell interference (ICI). The performance of a relay enhanced cellular system depends significantly on the resource allocation scheme, especially when taking into account the resource competition from different links. Therefore, in this work, an efficient and effective resource allocation and scheduling scheme based on the subframe structure is proposed to maximize the benefit of the shared relay. System level simulations quantify the system performance in different resource demand situations, and show that the deployment of shared relays can improve significantly the overall system performance and also increase the throughput of cell edge users as compared to the conventional separated cell edge relay station deployment.

As future small cell base stations (SCBSs) are set to be multi-mode capable (i.e., transmitting on both licensed and unlicensed bands), a cost-effective integration of both technologies coping with peak data demands is crucial. Using tools from reinforcement learning, a distributed cross-system traffic steering framework is proposed whereby SCBSs leverage WiFi, to autonomously optimize their long-term performance over the licensed spectrum band, as a function of the traffic load and users' heterogeneous Quality of Service (QoS) requirements. The proposed traffic steering solution is validated in a Long-Term Evolution (LTE) simulator augmented with WiFi hotspots. Remarkably, it is shown that the proposed cross-system learning-based approach outperforms several benchmark algorithms and traffic steering policies, with gains reaching up to 200% when using a traffic-aware scheduler as compared to the classical proportional fair (PF) scheduler.

The growth of energy consumption driven by a rise in traffic rate demand and services, requires cellular operators to extend their infrastructure to meet these demands. To address this issue, deployment of low power base stations (BSs) in traditional macrocells have recently being considered to offer high data rates and simultaneously reduce the load of the macrocellular networks. However, the massive and unplanned deployment of small cells and their uncoordinated operations raise important questions about the energy efficiency in the heterogeneous cellular networks. In this paper, the impact of deploying a number of pico BSs on the system performance of macrocellular network is investigated. We analyze the energy efficiency of the downlink macro-picocells heterogeneous network, measured by the traffic capacity divided by the power consumption of the BSs. An adaptive power control based on the iterative-waterfilling scheme has been implemented to control the power among the macro and the pico BSs. The numerical results show that the total macrocellular capacity improves as the number of pico stations increases, but the energy efficiency is improved only for a reasonable number of pico base stations. Moreover, the iterative-waterfilling power allocation scheme improves the energy efficiency even with introducing more pico base stations as compared with other power allocation schemes. This work provides essential understanding for successful deployment of power efficient heterogeneous networks.

In this paper, we focus on a half-duplex downlink cellular system with relay cooperation. We consider the beam-forming design problem with a limited amount of feedback for channel state information (CSI), which is only available at the receiver side. Based on this structure, we calculate the sum-rate lower bound when zero forcing (ZF) or eigen-beamforming is implemented at the macro base station and relay station. With the lower bound, we optimize the numbers of feedback bits for quantizing the desired and interfering channels and propose an adaptive beamforming strategy with limited feedback which selects a suitable beamforming scheme from ZF or eigen-beamforming based on the received interference and noise power level of the users. Simulation result shows that the bit partitioning algorithm outperforms the equal bit distribution scheme especially when the signal to noise ratio (SNR) is large. In addition, our proposed adaptive beamforming strategy outperforms existing schemes in different interference scenarios.

In this paper we consider a half-duplex multiple-input multiple-output (MIMO) cooperative amplify-and-forward (AF) relay network with multiple relay nodes. Firstly, we assume the channel state information (CSI) is available at all nodes to investigate the optimal source and relay beamforming vector design and relay selection. Based on this structure, a new scheme of limited feedback joint effective relay selection and beamforming vector design is proposed, which uses a new strategy to share channel information between relay and destination. This proposed scheme, which chooses the best relay and optimizes the beamforming vectors maximizing the received SNR, can significantly reduce the required number of feedback bits and maintain a suitable performance compared to the optimal non-practical solution. Simulation results show that our scheme approaches the performance of the scheme with full CSI assumption and outperforms conventional schemes, while having lower computational complexity and lower feedback delay. The cooperative diversity gain is also verified by the simulation result.

In this paper we investigate a two-cell downlink scenario with base station cooperation. We assume that a limited amount of feedback for channel state information (CSI) is available and optimize the numbers of bits for quantizing the desired and interfering channels. A cooperative beamforming strategy with limited feedback is proposed which selects suitable beamforming schemes from zero forcing (ZF) and eigen-beamforming based on the received interference and noise power level of the users. It is shown that the proposed cooperative strategy outperforms existing schemes in different interference scenarios.

In this paper, we investigate enhanced Inter-Cell Interference Coordination (e-ICIC) techniques for Heterogeneous Networks (HetNets), consisting of a mix of macro and picocells. We model this strategic coexistence as a multi-agent system in which decentralized interference management and cell association strategies inspired from Reinforcement Learning (RL) are devised. Specifically, we focus on time and frequency domain ICIC techniques in which picocells optimally learn their cell range bias and downlink transmit power allocation. In turn, the macrocell optimizes its transmission by serving its own users while adhering to the picocell interference constraint. To substantiate our theoretical findings, system level simulations are carried out in which our proposed solution is compared with a number of existing ICIC approaches, such as resource partitioning, fixed cell range expansion (CRE) and fixed Almost Blank Subframe (ABS). Interestingly, our proposed solution is shown to yield substantial gains of up to 125% compared to static ICIC approaches.

Coordinated multipoint transmission (CoMP) is considered for a heterogeneous network where different kinds of base stations (BS) are located. We focus on linear transceiver design with the goal of maximizing the weighted sum rate in the downlink of a multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) system. The problem is shown to be non-convex, thus, the problem of finding the global optimum is an intrinsically intractable, NP hard problem. We propose an algorithm which divides the main problem into several convex subproblems, and, is shown to provide efficient suboptimal solutions.

Autonomous interference management solutions for inter-cell interference coordination (ICIC) are of utmost importance. In this paper, the coexistence between macro and small cells is studied whereby different ICIC techniques pertaining to different deployment and information assumptions are evaluated. Inspired from Evolutionary Game Theory (EGT), decentralized strategies are devised, in which small cell Base Stations (BSs) exchange information through a central controller, and adapt their strategies based on instantaneous and average payoffs of the small cell population. In contrast, when distributed operation is aimed at, using tools from Reinforcement Learning (RL) small cells learn by interacting with their environment through trials and-errors, and autonomously optimize their strategies based on a mere feedback. In particular, we compare the performance of decentralized Q- learning, Fuzzy Q-learning, improved Q-learning and expertness-based Q-learning procedures. Finally, the overall performance of the network in terms of average peruser data throughput and convergence are carried out in an LTE-A system level simulator.

We investigate the resource allocation problem for the downlink of a spatial multiplexing (SM) based multiple input multiple output orthogonal frequency division multiple access (MIMO-OFDMA) based network. We address this problem in the context of the utility-based resource allocation presented in earlier papers in order to enhance the efficiency and guarantee fairness among users by exploiting multiuser diversity, frequency diversity, as well as time diversity. We design utility functions with respect to the average rate in order to simultaneously provide two services, real-time and best-effort. We propose a low-complexity joint subchannel and power control algorithm that converges very fast. Simulation results indicate that using the proposed method achieves near-optimum solutions and the available resources are distributed more fairly among users.

This paper presents a framework of maximum-a-posteriori (MAP) algorithms for the automatic modulation classification (AMC) in orthogonal frequency division multiplexing (OFDM) based communication systems with adaptive modulation (AM). The proposed classifiers intensively utilize side information typically available in wireless time-division duplex (TDD) systems that is channel reciprocity, the known frame structure and the knowledge about the total transmission data rate. As the computational complexity of the optimal algorithms is rather high, a metric approximation is used whose accuracy increases with rising signal-to-noise power ratio (SNR). Numerical results show that the system performance degradation in terms of the packet-error ratio (PER) due to erroneously detected modulation schemes is small in typical wireless communication scenarios if the proposed AMC algorithm is applied.

Iterative layered space time (ILST) architectures have been proven to be a promising detection technique for Single-Carrier (SC) MIMO (multiple-input multiple-output) systems. Interference cancellation is applied successively in an ILST receiver by feeding back the detected symbols. In this paper, we analyze the imperfect decision feedback for an ILST receiver. The purpose is to figure out whether the system performance is improved or degrades by unreliable decision feedback. The analytical comparison shows that if the feedback layer and the detecting layer are weighted correlated, the decision feedback always improves the SNIR performance. For the decision feedback from the current layer itself, it improves the performance with probability nearly to 1 in frequency selective channels. This theoretical result coincides with the simulation results.

In a wireless networked control system (WNCS), physical processes are periodically observed and corresponding single analog measurements are digitized by scalar quantizers. Subsequently, these data are transmitted via a digital wireless communication system. A new source/channel coding scheme is presented that achieves a very low mean square error (MSE) of the analog physical values when they are transmitted over a noisy channel. The use of a quantizer with natural binary code (NBC) labeling is proposed and it is shown that a certain class of linear unequal error protection (LUEP) block codes which are obtained from convolutional codes by direct truncation (DT) termination, matches the source characteristics of this kind of quantizer and leads to a low MSE. The LUEP capabilities of such codes are examined and simulation results are presented that show that such codes outperform standard block codes as well as Ma's generalized tail-biting (GTB) codes. Additionally, we provide examples where convolutional encoded quantizer outputs also show superior performance compared to redundant index assignments which are obtained from spread s snake-in-the-box (SIB) codes. Furthermore, by means of a special class of time-varying convolutional codes, we develop a method for the bitwise adjustment of the protection levels of an LUEP block code, which may be used to adapt the code to the channel.

This paper investigates a novel efficient automatic modulation classification (AMC) algorithm in wireless time division duplex (TDD) orthogonal frequency division multiplexing (OFDM) systems with adaptive modulation (AM). Starting from the well-known maximum-likelihood (ML) classification metric for digital quadrature amplitude modulation (QAM) schemes, partial channel reciprocity in TDD-based adaptive OFDM systems is exploited by applying the maximum-a-posteriori (MAP) principle. A heuristic approach to find the required occurrence probabilities of the selected modulation schemes in a time-variant radio channel is analyzed. In order to reduce the overall computational complexity, a simplified metric is presented that is suitable for the implementation in real-time operating systems. Numerical results in terms of classification error probabilities confirm the effectivity of the complexity reductions. Moreover, it is demonstrated that the influence of the performance degradation on the overall packet error ratios (PER) due to imperfect modulation classification is small in a typical wireless communication scenario.

This paper presents a novel automatic modulation classification (AMC) algorithm in wireless time division duplex (TDD) orthogonal frequency division multiplexing (OFDM) systems with adaptive modulation (AM). Based upon the maximum-a-posteriori (MAP) criterion, a classification method for digital quadrature amplitude modulation (QAM) schemes is developed that exploits the channel reciprocity in TDD systems and the receiver knowledge about the overall transmission data rate. The AMC algorithm enables the application of adaptive modulation in wireless OFDM systems without loss in the effective data rate caused by signaling of the bit allocation table (BAT). Numerical results show almost no performance loss in terms of the packet error ratio (PER) compared to the case with perfect knowledge of the modulation schemes if the proposed AMC technique is used.

This paper introduces new joint estimation methods of multiple carrier frequency offsets (CFOs) and channel impulse responses (CIR) in application to multiuser orthogonal frequency division multiplexing (OFDM) systems. The estimators are derived from the optimal maximum-likelihood (ML) principle. Complexity reductions are achieved by exploiting the correlation properties of the training sequence (TS). The grid search algorithm is converted into a polynomial root finding procedure which leads to low-complexity closed-form estimators for moderate CFOs. Furthermore, iterative estimators for larger CFOs are proposed. Numerical results confirm that the performance degradation due to the approximations compared to the Cramer-Rao bound (CRB) is small and may be negligible in practice.

This paper considers the practical multiple-input multiple-output systems with orthogonal frequency division multiplexing (MIMO-OFDM) and bit-interleaved coded modulation (BICM) in spatially correlated broadband channels. Using link adaption techniques, the MIMO scheme that better exploits the space and frequency characteristics of the encountered channel condition is selected. It is shown that the bandwidth efficiency is increased compared to systems with fixed MIMO schemes in all propagation scenarios, while maintaining a predefined link quality. Furthermore, the adaptive transmission in channels with low spatial correlation can attain the complete multiplexing gain, whereas the finite set of modulation and coding schemes restricts the multiplexing gain that can be extracted when the spatial correlation is large.

This contribution considers the estimation and compensation of residual multiple carrier frequency offsets (CFOs) and sampling frequency offsets (SFOs) in the uplink of multiuser OFDM systems. Based on the observation of a user-dependent phase rotation, an approximate maximum-likelihood (ML) estimator is proposed in order to estimate the CFOs and SFOs and to track the phase in a post-synchronization step. By using a Taylor approximation, the estimation complexity is reduced. Bit error-ratio (BER) simulations show that the system performance degradation due to (small) frequency mismatches is negligible if the proposed method is applied.

This contribution presents an adaptive MIMO transmission scheme for packet-switched broadband OFDM wireless communications with bit-interleaved coded modulation (BICM). Combining EESM-based link adaptation and per antenna rate control (PARC), the proposed scheme adapts the MIMO transmission method between beamforming and spatial multiplexing to the spatial correlation of the encountered wireless channel. This scheme aims to maximize the average bandwidth efficiency for a predefined target packet error ratio (PER) and transmit energy. Moreover, additional performance gains are demonstrated when adaptive bit-loading algorithm is implemented.

A new approach to multi-antenna downlink beam- forming is proposed that provides an improved robustness against uncertainty in the downlink channel covariance matrices caused by errors between the actual and estimated channel values. The proposed method uses the knowledge of the statistical distribution of such a covariance uncertainty to minimize the total downlink transmit power under the constraint that the outage probability does not exceed a certain threshold value. Although our approach initially leads to a non-convex optimization problem, it can be reformulated in a convex form using the semidefinite relaxation technique. The resulting convex optimization problem can be solved efficiently using the well-established interior point methods. Computer simulations verify performance improvements of the proposed technique as compared to the robust transmit beamforming method based on the worst-case performance optimization with judicious selection of the upper bounds on channel covariance errors.

This contribution proposes a new joint estimation method of multiple carrier frequency offsets (CFOs) and channels in the uplink of multiuser orthogonal frequency division multiplexing (OFDM) systems. The estimators are derived from the optimal maximum-likelihood (ML) principle. Complexity reductions are achieved by exploiting the correlation properties of the training-sequence. The grid search algorithm is converted into a polynomial root finding procedure which leads to closed-form estimators for moderate CFOs. Numerical results confirm that the performance degradation due the approximations compared to the Cramer-Rao bound (CRB) is small and may be negligible in practice

A multi-user multiple-input-multiple-output (MIMO) system with orthogonal space-time block coding (OSTBC) is analyzed in a Rayleigh fading environment for the uplink of a wireless communication system. The outage probability of the signal-to-interference-and-noise ratio (SINR) for the user of interest is evaluated by using the following linear receivers; 1) a sub-optimum matched filter (MF) and 2) an optimum minimum variance (MV) receiver. Simulation results show that for an outage probability of 0.2, the MV receiver provides a gain of about 3 dB over the MF in terms of the SINR threshold value when a full-rate OSTBC like the Alamouti code is used. However, for low-rate OSTBCs like a 1/2-rate 8times3 OSTBC, the difference of this gain between the MF and the MV receiver is above 8 dB

This contribution considers the estimation and compensation of residual multiple carrier frequency offsets (CFOs) and sampling frequency offsets (SFOs) in the uplink of a multiuser OFDM system. Based on the observation of a user-dependent phase rotation, an approximate maximum-likelihood (ML) estimator is proposed in order to estimate the CFOs and SFOs to track the phase in a post-synchronization step. Bit-error-ratio (BER) simulations show that the system performance degradation due to (small) frequency mismatches is negligible if the proposed method is applied

A multi-user Multiple Input Multiple Output (MIMO) system with beamforming based on Maximum Ratio Transmission (MRT) is analyzed in a Rayleigh fading environment. A simple closed and compact form approximate expression for the outage probability of a mobile station for the downlink of such a system is obtained by considering that all the mobile stations are power controlled by a single base station. An interesting observation of the analysis is that an optimum power control problem can be formulated based on the outage probability of each mobile station in the downlink because the outage probability computation is easily simplified for a cellular environment where all the mobile stations are power controlled by the single base station. The objective is to minimize the base station transmission power by keeping the outage probability of all mobile stations below a specified threshold value. The optimization problem is non-convex and non-linear. We use an Evolutionary Strategy (EV) [1] to solve such a non-convex optimization problem.

In this paper, we propose a new uplink beamforming algorithm that provides robustness against the uncertainty of the assumed spatial covariance matrix at a base station (BS) which employs antenna arrays. This uncertainty arises due to the difference between the presumed and the actual array response as well as the estimation errors of the fading coefficients. In our method, we exploit the assumed statistical distribution of the uncertainty to minimize the outage probability of each mobile station in the uplink. Our approach leads to a semidefinite relaxation problem that can be solved efficiently using the well-established interior point methods. Simulation results show that our method slightly outperforms the robust adaptive beamforming based upon worst-case performance optimization. Moreover, the proposed technique avoids the necessity of the knowledge of the norm bounds of the uncertainty of spatial covariance matrices.

We propose a new uplink to downlink spatial covariance matrix transformation technique that provides robustness against uplink steering vector mismatches for frequency duplex systems (FDD) in a frequency selective fading environment. Our approach leads to a matrix robust least squares (RLS) problem that can be formulated in a convex form as a second order cone (SOC) program and solved efficiently using the well-established interior point methods. The performance of the proposed method is compared with that of (K. Hugl et al., 1999) and (T. Aste et al., 1998) using a dynamic system level simulator developed for investigating the capacity improvement of a UMTS-FDD system with smart antennas at the base stations. Downlink capacity is used as a measure of system performance by finding the number of users for which a certain quality of service (QoS) requirement is fulfilled. System level simulations are carried out for 4-element uniform circular antenna (UCA) array. Simulation results show that our method outperforms both (K. Hugl et al., 1999) and (T. Aste et al., 1998) by supporting about 48% and 15% more average number of users than that of (K. Hugl et al., 1999) and (T. Aste et al., 1998) , respectively without any significant degradation in performance when compared to (T. Aste et al., 1998) with known uplink steering vector.

This paper presents a comparison of two different uplink to downlink covariance matrix transformation methods that can be used in downlink beamforming for frequency selective FDD channels. The performance improvement obtained from the transformation methods is compared with that from the method, which directly uses the uplink covariance matrix for downlink beamforming. For this purpose, a dynamic system level simulator developed for investigating the capacity improvement of a UMTS-FDD system employing smart antennas at the base stations is used. Downlink capacity is used as a measure of the performance of the system by finding the number of users for which a certain quality of service (QoS) requirement is fulfilled. System level simulations are carried out for antenna arrays with 2, 4 and 8 elements. Simulation results show that the downlink capacity can be improved significantly with higher number of antenna elements only if a transformation method is used in order to overcome the effect of different uplink and downlink carrier frequencies.

A new dynamic system level simulator is developed for investigating the capacity improvement in a UMTS-FDD system employing smart antennas at the base stations. The simulator is used to analyze the performance of this system by finding the number of users for which a certain quality of service (QoS) requirement is fulfilled. In this paper, analyses of the downlink capacity for different numbers of array elements with different adaptive beamforming strategies are presented. When using smart antennas, the real amount of performance improvement can only be estimated by system level simulations. Hence, dynamic system level simulations for UMTS-FDD are carried out which take into account the statistical nature of almost all parameters, e.g. wave propagation, user motion and traffic scenarios. Simulation results show a significant system capacity increase when beamforming is utilized.

In the paper downlink beamforming for cellular radio systems with frequency division duplexing (FDD) is investigated. System level simulations clarify what gain can be achieved by applying circular arrays with omnidirectional antenna elements in contrast to linear arrays with sectorizing antenna elements.

The capacity of cellular mobile radio systems can be increased with smart antennas. The following two concepts can be utilized. First, smart antennas enable the concept of space division multiple access (SDMA) so that transmission from a base station to several mobiles at the same time and carrier frequency is possible. Second, cochannel interference in cellular systems can be reduced so that the frequency reuse is improved. The purpose of downlink beamforming is to transmit as much power as possible to the desired mobile and as little power as possible to any undesired mobile. In the case of systems with frequency division duplex (FDD) the fast fading processes for uplink and downlink are different. But, if the frequency separation is not too large, the uplink and downlink waves exhibit the same directional dependence. Therefore, downlink beamforming has to be carried out in an average sense based on the uplink channel measurements. The paper discuss the optimization of downlink beamforming for systems with FDD. It answers the question whether beamforming should be optimized in such a way that the transmitted power is mainly sent into the direction of the path with minimum average attenuation or whether it is better to distribute the power to all desired paths. The advantage from concentrating the power to the main path is that the interference power to other mobiles may be reduced due to a higher degree of freedom for beamforming. In the case of power distribution on all paths, the advantage from higher path diversity may be obtained.