A Linear Multi-User Detector for STBC MC-CDMA Systems based on the Adaptive Implementation of the Minimum-Conditional Bit-Error-Rate Criterion and on Genetic Algorithm-assisted MMSE Channel Estimation

The implementation of efficient baseband receivers characterized by affordable computational load is a crucial point in the development of transmission systems exploiting diversity in different domains. In this paper, we are proposing a linear multi-user detector for MIMO MC-CDMA systems with Alamouti’s Space-Time Block Coding, inspired by the concept of Minimum Conditional Bit-Error-Rate (MCBER) and relying on Genetic-Algorithm (GA)-assisted MMSE channel estimation. The MCBER combiner has been implemented in adaptive way by using Least-Mean-Square (LMS) optimization. Firstly, we shall analyze the proposed adaptive MCBER MUD receiver with ideal knowledge of Channel Status Information (CSI). Afterwards, we shall consider the complete receiver structure, encompassing also the non-ideal GA-assisted channel estimation. Simulation results evidenced that the proposed MCBER receiver always outperforms state-of-the-art receiver schemes based on EGC and MMSE criterion exploiting the same degree of channel knowledge (i.e. ideal or estimated CSI)

A genetic algorithm-assisted semi-adaptive MMSE multi-user detection for MC-CDMA mobile communication systems

In this work, a novel Minimum-Mean Squared-Error (MMSE) multi-user detector is proposed for MC-CDMA transmission systems working over mobile radio channels characterized by time-varying multipath fading. The proposed MUD algorithm is based on a Genetic Algorithm (GA)-assisted per-carrier MMSE criterion. The GA block works in two successive steps: a training-aided step aimed at computing the optimal receiver weights using a very short training sequence, and a decision-directed step aimed at dynamically updating the weights vector during a channel coherence period. Numerical results evidenced BER performances almost coincident with ones yielded by ideal MMSE-MUD based on the perfect knowledge of channel impulse response. The proposed GA-assisted MMSE-MUD clearly outperforms state-of-the-art adaptive MMSE receivers based on deterministic gradient algorithms, especially for high number of transmitting users

A Near-Optimum Multiuser Receiver for STBC MC-CDMA Systems Based on Minimum Conditional BER Criterion and Genetic Algorithm-Assisted Channel Estimation

The implementation of efficient baseband receivers characterized by affordable computational load is a crucial point in the development of transmission systems exploiting diversity in different domains. This would be a crucial point in the future development of 4G systems, where space, time, and frequency diversity will be combined together in order to increase system throughput. In this framework, a linear multiuser detector for MC-CDMA systems with Alamouti's Space-Time Block Coding (STBC), which is inspired by the concept of Minimum Conditional Bit Error Rate (MCBER), is proposed. The MCBER combiner has been implemented in adaptive way by using Least-Mean-Square (LMS) optimization. The estimation of Channel State Information (CSI), necessary to make practically feasible the MCBER detection, is aided by a Genetic Algorithm (GA). The obtained receiver scheme is near-optimal, as both LMS-based MCBER and GA-assisted channel estimation perform closely to optimum in fulfilling their respective tasks. Simulation results evidenced that the proposed receiver always outperforms state-of-the-art receiver schemes based on EGC and MMSE criterion exploiting the same degree of channel knowledge

Is There Light at the Ends of the Tunnel? Wireless Sensor Networks for Adaptive Lighting in Road Tunnels

Existing deployments of wireless sensor networks (WSNs) are often conceived as stand-alone monitoring tools. In this paper, we report instead on a deployment where the WSN is a key component of a closed-loop control system for adaptive lighting in operational road tunnels. WSN nodes along the tunnel walls report light readings to a control station, which closes the loop by setting the intensity of lamps to match a legislated curve. The ability to match dynamically the lighting levels to the actual environmental conditions improves the tunnel safety and reduces its power consumption. The use of WSNs in a closed-loop system, combined with the real-world, harsh setting of operational road tunnels, induces tighter requirements on the quality and timeliness of sensed data, as well as on the reliability and lifetime of the network. In this work, we test to what extent mainstream WSN technology meets these challenges, using a dedicated design that however relies on wellestablished techniques. The paper describes the hw/sw architecture we devised by focusing on the WSN component, and analyzes its performance through experiments in a real, operational tunnel

Situation-Aware Radio Resource Management for Multi-Rate MC-CDMA Wireless Networks Targeted at Multimedia Data Exchanges in Local Areas

In this report, a novel methodology for radio resource management is considered for multi-rate MC-CDMA WLAN indoor networking. The proposed strategy is based on resource reallocation and rate adaptation depending on the network situation, monitored in terms of achieved QoS by an intelligent access-point (AP). As they access the medium, all users send bit-rate requests on the basis of their application requirements. Then, the AP monitors the QoS in terms of frame-error-rate (FER) and decides a) to reallocate the radio resources (in terms of number of orthogonal subchannels) and b) to reduce the data rate, in order to improve throughput performances for those users penalized by heavy FER. The “rate downshift” process is continued until the FER measured by the AP allows data transfer with an acceptable QoS. The intelligent AP can also issue a “rate upshift” for users previously downshifted, or in presence of explicit requests, when the channel situation improves. Simulation results underline a general improvement of the aggregated throughput deriving from adaptively manage the QoS requirements with respect to the network situation, thus enabling good resource usage with the WLAN cell

Genetic Algorithm-assisted Maximum-Likelihood Multi-user Detection for Multi-Rate MC-CDMA Systems

In this letter , the use of Genetic Algorithms (GAs) has been investigated in order to implement a computationally tractable Multi-User Detection (MUD) for synchronous multi-rate Multi-Carrier-Code-Division-Multiple-Access (MR MC-CDMA) systems. It is known that MC-CDMA performances can be seriously limited by multi-user interference. This is particularly true in the case of multi-rate systems where some users could exploit a reduced diversity against multipath channel distortions. The use of Genetic Algorithms (GAs) is therefore proposed as a sub-optimal solution to the MUD problem in a multi-rate Variable-Spreading-Length (VSL) MC-CDMA downlink transmission. A set of selected numerical experiments have been reported and discussed in order to assess the capability of the proposed GA-based approach. The reported results, obtained with an affordable computational burden, have shown a near-optimum behavior of the proposed GA-based MUD

Study and Development of Novel Techniques for PHY-Layer Optimization of Smart Terminals in the Context of Next-Generation Mobile Communications

Future mobile broadband communications working over wireless channels are required to provide high performance services in terms of speed, capacity, and quality. A key issue to be considered is the design of multi-standard and multi-modal ad-hoc network architectures, capable of self-configuring in an adaptive and optimal way with respect to channel conditions and traffic load. In the context of 4G-wireless communications, the implementation of efficient baseband receivers characterized by affordable computational load is a crucial point in the development of transmission systems exploiting diversity in different domains. This thesis proposes some novel multi-user detection techniques based on different criterions (i.e., MMSE, ML, and MBER) particularly suited for multi-carrier CDMA systems, both in the single- and multi-antenna cases. Moreover, it considers the use of evolutionary strategies (such as GA and PSO) to channel estimation purposes in MIMO multicarrier scenarios. Simulation results evidenced that the proposed PHY-layer optimization techniques always outperform state of the art schemes by spending an affordable computational burden. Particular attention has been used on the software implementation of the formulated algorithms, in order to obtain a modular software architecture that can be used in an adaptive and optimized reconfigurable scenario

SUMO 2016 – Traffic, Mobility, and Logistics

Dear reader, You are holding in your hands a volume of the series „Reports of the DLR-Institute of Transportation Systems“. We are publishing in this series fascinating, scientific topics from the Institute of Trans- portation Systems of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e.V. – DLR) and from his environment. We are providing libraries with a part of the circulation. Outstanding scientific contributions and dissertations are here published as well as projects reports and proceedings of conferences in our house with different contributors from science, economy and politics. With this series we are pursuing the objective to enable a broad access to scientific works and results. We are using the series as well as to promote practically young researchers by the publication of the dissertation of our staff and external doctoral candidates, too. Publications are important milestones on the academic career path. With the series „Reports of the DLR-Institute of Transportation Systems / Berichte aus dem DLR-Institut für Verkehrssystemtechnik“ we are widening the spectrum of possible publications with a building block. Beyond that we understand the communication of our scientific fields of research as a contribution to the national and international research landscape in the fields of automotive, railway systems and traffic management. With this volume we publish the proceedings of the SUMO Conference 2016 which was held from 23rd to 25th May 2016 with a focus on traffic, mobility, and logistics. SUMO is an open source tool for traffic simulation that provides a wide range of traffic planning and simulation functionalities.The conference proceedings offer an overview of the applicability of the SUMO tool suite as well as its universal extensibility due to the availability of the source code. The major topic of this fourth edition of the SUMO conference are the different facets of moving objects occurring as personal mobility and freight delivery as well as communicating networks of intelligent vehicles. Several articles cover heterogeneous traffic networks, junction control and new traffic model extensions to the simulation. Subsequent specialized issues such as disaster management aspects and applying agile development techniques to scenario building are targeted as well. At the conference the international user community exchanged their experiences in using SUMO. With this volume we provide an insight to these experiences as inspiration for further projects with the SUMO suite