Studies on 6-sector-site deployment in downlink LTE

Mobile data traffic is expected to increase massively in the following years. Consequently, service operators are induced to increase the capacity of their networks continually to attract more subscribers and maximize their revenues. At the same time, they want to minimize operational costs and capital expenditures. Among the alternatives that aim to increase the network capacity, higher order sectorization, and in particular a six sectorized configuration, is nowadays attracting a lot of attention for LTE macro-cell deployments since a higher number of sectors per site results in improved site capacity and coverage. A six sectorized configuration is attractive for both roll-out phase and growth phase of the network. In the roll-out phase, the radio access network is planned with 6-sector sites instead of 3-sector sites with the advantage that less sites are needed for the same capacity and coverage requirements. In the growth phase, the six sectorized configuration can be used to upgrade existing 3-sector sites where the traffic grows beyond the current sites' capabilities. Therefore, no additional expensive and time consuming contracts need to be signed for the locations of the new sites, while the existing sites are used more efficiently. However, although potentially a 6-sector site can offer a double capacity than a 3-sector site, several factors prevent the capacity from growing proportionately to the number of sectors. Consequently, there is an uncertainty on whether the capacity gain is high enough to justify the extra costs of the additional equipment and, more specifically, whether the 6-sector-site deployment is more economically attractive than a 3-sector-site deployment. The aim of this report is to solve this uncertainty. First, we present the main factors that affect the capacity gain. Next, we quantify the impact of these factors on the capacity gain in downlink LTE with the use of a system level simulator. Finally, we use the results of the simulation study as inputs for an economic study to access the reasons for a possible deployment of 6-sector sites instead of 3-sector sites for LTE

Resource Allocation, Scheduling and Feedback Reduction in Multiple Input Multiple Output (MIMO) Orthogonal Frequency-Division Multiplexing (OFDM) Systems

The number of wireless systems, services, and users are constantly increasing and therefore the bandwidth requirements have become higher. One of the most robust modulations is Orthogonal Frequency-Division Multiplexing (OFDM). It has been considered as an attractive solution for future broadband wireless communications. This dissertation investigates bit and power allocation, joint resource allocation, user scheduling, and limited feedback problem in multi-user OFDM systems. The following dissertation contributes to improved OFDM systems in the following manner. (1) A low complexity sub-carrier, power, and bit allocation algorithm is proposed. This algorithm has lower computational complexity and results in performance that is comparable to that of the existing algorithms. (2) Variations of the proportional fair scheduling scheme are proposed and analyzed. The proposed scheme improves system throughput and delay time, and achieves higher throughput without sacrificing fairness which makes it a better scheme in terms of efficiency and fairness. (3) A DCT feedback compression algorithm based on sorting is proposed. This algorithm uses sorting to increase the correlation between feedback channel quality information of frequency selective channels. The feedback overhead of system is successfully reduced

Multi-user MIMO wireless communications

Mehrantennensysteme sind auf Grund der erhöhten Bandbreiteneffizienz und Leistung eine Schlüsselkomponente von Mobilfunksystemen der Zukunft. Diese ermöglichen das gleichzeitige Senden von mehreren, räumlich getrennten Datenströmen zu verschiedenen Nutzern. Die zentrale Fragestellung in der Praxis ist, ob der ursprünglich vorausgesagte Kapazitätsgewinn in realistischen Szenarios erreicht wird und welche spezifischen Gewinne durch zusätzliche Antennen und das Ausnutzen von Kanalkenntnis am Sender und Empfänger erzielt werden, was andererseits einen Zuwachs an Overhead oder nötiger Rechenleistung bedeutet. In dieser Arbeit werden neue lineare und nicht-lineare MU-MIMO Precoding- Verfahren vorgestellt. Der verfolgte Ansatz zur Bestimmung der Precoding- Matrizen ist allgemein anwendbar und die entstandenen Algorithmen können zur Optimierung von verschiedenen Kriterien mit beliebig vielen Antennen an der Mobilstation eingesetzt werden. Das wurde durch die Berechnung der Precoding- Matrix in zwei Schritten erreicht. Im ersten Schritt wird die Überschneidung der Zeilenräume minimiert, die durch die effektiven Kanalmatrizen verschiedener Nutzer aufgespannt werden. Basierend auf mehreren parallelen Einzelnutzer-MIMO- Kanälen wird im zweiten Schritt die Systemperformanz bezüglich bestimmter Kriterien optimiert. Aus der gängigen Literatur ist bereits bekannt, dass für Nutzer mit nur einer Antenne das MMSE Kriterium beim precoding optimal aber nicht bei Nutzern mit mehreren Antennen. Deshalb werden in dieser Arbeit zwei neue Mehrnutzer MIMO Strategien vorgestellt, die vom MSE Kriterium abgeleitet sind, nämlich sukzessives MMSE und RBD. Bei der sukzessiven Verarbeitung mit einer entsprechenden Anpassung der Sendeleistungsverteilung kann die volle Diversität des Systems ausgeschöpft werden. Die Kapazität nähert sich dabei der maximalen Summenrate des Systems an. Bei gemeinsamer Verarbeitung der MIMO Kanäle wird unabhängig vom Grad der Mehrnutzerinterferenz die maximale Diversität erreicht. Die genannten Techniken setzen entweder eine aktuelle oder eine über einen längeren Zeitraum gemittelte Kanalkenntnis voraus. Aus diesem Grund müssen die Auswirkungen von Kanal-Schätzfehlern und Einflüsse des Transceiver Front-Ends auf die Verfahren näher untersucht werden. Für eine weitergehende Abschätzung der Mehrantennensysteme muss die Performanz des Gesamtsystems untersucht werden, da viele Einflüsse auf die räumliche Signalverarbeitung bei Betrachtung eines einzelnen Links nicht erkennbar sind. Es wurde gezeigt, dass mit MIMO Precoding Strategien ein Vielfaches der Datenrate eines Systems mit nur einer Antenne erzielt werden kann, während der Overhead durch Pilotsymbole und Steuersignale nur geringfügig zunimmt.Multiple-input, multiple-output (MIMO) systems are a key component of future wireless communication systems, because of their promising improvement in terms of performance and bandwidth efficiency. An important research topic is the study of multi-user (MU) MIMO systems. Such systems have the potential to combine the high throughput achievable with MIMO processing with the benefits of space division multiple access (SDMA). The main question from a practical standpoint is whether the initially predicted capacity gains can be obtained in more realistic scenarios and what specific gains result from adding more antennas and overhead or computational power to obtain channel state information (CSI) at the transceivers. In this thesis we introduce new linear and non-linear MU MIMO processing techniques. The approach used for the design of the precoding matrix is general and the resulting algorithms can address several optimization criteria with an arbitrary number of antennas at the user terminals (UTs). This is achieved by designing the precoding matrices in two steps. In the first step we minimize the overlap of the row spaces spanned by the effective channel matrices of different users. In the next step, we optimize the system performance with respect to the specific optimization criterion assuming a set of parallel single-user MIMO channels. As it was previously reported in the literature, minimum mean-squared-error (MMSE) processing is optimum for single-antenna UTs. However, MMSE suffers from a performance loss when users are equipped with more than one antenna. The two MU MIMO processing techniques that result from the two different MSE criteria that are proposed in this thesis are successive MMSE and regularized block diagonalization. By iterating the closed form solution with appropriate power loading we are able to extract the full diversity in the system and empirically approach the maximum sum-rate capacity in case of high multi-user interference. Joint processing of MIMO channels yields maximum diversity regardless of the level of multi-user interference. As these techniques rely on the fact that there is either instantaneous or long- term CSI available at the base station to perform precoding and decoding, it was very important to investigate the influence of the transceiver front-end imperfections and channel estimation errors on their performance. For a comprehensive assessment of multi-antenna techniques, it is mandatory to consider the performance at system level, since many effects of spatial processing are not tractable at the link level. System level investigations have shown that MU MIMO precoding techniques provide several times higher data rates than single-input single-output systems with only slightly increased pilot and control overhead