Dirk Wübben

MMSE extension of V-BLAST based on sorted QR decomposition

In rich-scattering environments, layered space-time architectures like the BLAST system may exploit the capacity advantage of multiple antenna systems. We present a novel, computationally efficient algorithm for detecting V-BLAST architectures with respect to the MMSE criterion. It utilizes a sorted QR decomposition of the channel matrix and leads to a simple successive detection structure. The new algorithm needs only a fraction of computational effort compared to the standard V-BLAST algorithm and achieves the same error performance.

Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction

In recent publications the use of lattice-reduction for signal detection in multiple antenna systems has been proposed. In this paper, we adopt these lattice-reduction-aided schemes to the MMSE criterion. We show that an obvious way to do this is infeasible and propose an alternative method based on an extended system model, which in conjunction with simple successive interference cancellation nearly reaches the performance of maximum-likelihood detection. Furthermore, we demonstrate that, a sorted QR decomposition can significantly reduce the computational effort associated with lattice-reduction. Thus, the new algorithm clearly outperforms existing methods with comparable complexity.

Cloud technologies for flexible 5G radio access networks

The evolution toward 5G mobile networks will be characterized by an increasing number of wireless devices, increasing device and service complexity, and the requirement to access mobile services ubiquitously. Two key enablers will allow the realization of the vision of 5G: very dense deployments and centralized processing. This article discusses the challenges and requirements in the design of 5G mobile networks based on these two key enablers. It discusses how cloud technologies and flexible functionality assignment in radio access networks enable network densification and centralized operation of the radio access network over heterogeneous backhaul networks. The article describes the fundamental concepts, shows how to evolve the 3GPP LTE architecture, and outlines the expected benefits.

Reduced complexity MMSE detection for BLAST architectures

Theoretical and experimental studies have shown that layered space-time architectures like the BLAST system can exploit the capacity advantage of multiple antenna systems in rich-scattering environments. We present a new efficient algorithm for detecting such architectures with respect to the MMSE criterion. This algorithm utilizes a sorted QR decomposition of the channel matrix and leads to a simple successive detection structure. The algorithm needs only a fraction of the computational effort compared to the standard V-BLAST algorithm and achieves the same bit error performance.

Benefits and Impact of Cloud Computing on 5G Signal Processing: Flexible centralization through cloud-RAN

Cloud computing draws significant attention in the information technology (IT) community as it provides ubiquitous on-demand access to a shared pool of configurable computing resources with minimum management effort. It gains also more impact on the communication technology (CT) community and is currently discussed as an enabler for flexible, cost-efficient and more powerful mobile network implementations. Although centralized baseband pools are already investigated for the radio access network (RAN) to allow for efficient resource usage and advanced multicell algorithms, these technologies still require dedicated hardware and do not offer the same characteristics as cloud-computing platforms, i.e., on-demand provisioning, virtualization, resource pooling, elasticity, service metering, and multitenancy. However, these properties of cloud computing are key enablers for future mobile communication systems characterized by an ultradense deployment of radio access points (RAPs) leading to severe multicell interference in combination with a significant increase of the number of access nodes and huge fluctuations of the rate requirements over time. In this article, we will explore the benefits that cloud computing offers for fifth-generation (5G) mobile networks and investigate the implications on the signal processing algorithms.

MMSE-based lattice-reduction for near-ML detection of MIMO systems

Recently the use of lattice-reduction for signal detection in multiple antenna systems has been proposed. In this paper, we adopt these lattice-reduction aided schemes to the MMSE criterion. We show that an obvious way to do this is suboptimum and propose an alternative method based on an extended system model. In conjunction with simple successive interference cancellation this scheme almost reaches the performance of maximum-likelihood detection. Furthermore, we demonstrate that the application of sorted QR decomposition (SQRD) as a initialization step can significantly reduce the computational effort associated with lattice-reduction. Thus, the new algorithm clearly outperforms existing methods with comparable complexity.

Fronthaul and backhaul requirements of flexibly centralized radio access networks

Cloud radio access networks promise considerable benefits compared to decentralized network architectures, but they also put challenging requirements on the fronthaul and backhaul network. Flexible centralization can relax these requirements by adaptively assigning different parts of the processing chain to either the centralized baseband processors or the base stations based on the load situation, user scenario, and availability of fronthaul links. In this article, we provide a comprehensive overview of different functional split options and analyze their specific requirements. We compare these requirements to available fronthaul technologies, and discuss the convergence of fronthaul and backhaul technologies. By evaluating the aggregated fronthaul traffic, we show the benefits of flexible centralization and give guidelines on how to set up the fronthaul network to avoid over- or under-dimensioning.

Towards a flexible functional split for cloud-RAN networks

Very dense deployments of small cells are one of the key enablers to tackle the ever-growing demand on mobile bandwidth. In such deployments, centralization of RAN functions on cloud resources is envisioned to overcome severe inter-cell interference and to keep costs acceptable. However, RAN back-haul constraints need to be considered when designing the functional split between RAN front-ends and centralized equipment. In this paper we analyse constraints and outline applications of flexible RAN centralization.

Multi-User Pre-Processing in Multi-Antenna OFDM TDD Systems with Non-Reciprocal Transceivers

The combination of OFDM with joint pre-processing in adaptive multi-antenna systems offers both an ease of equalization in frequency-selective channels and keeping the signal processing at the mobile stations simple. In addition, the spatial dimension can be efficiently exploited to ensure high system throughput. With the utilization of higher-order modulation the performance of the system is highly sensitive to multiple access interference and nonorthogonal subchannels due to hardware impairments or insufficient adaptation to the current channel conditions. A further source of error in TDD systems are the non-reciprocal transceivers inhibiting the baseband-to-baseband channel reciprocity required for accurate channel state acquisition based on the uplink channel estimate. In this paper, measurement results of a low-cost hardware-based calibration are presented and the drawbacks are discussed leading to the utilization of a recently introduced relative calibration. The latter is applied to an OFDM system and achieves or at least approximates the baseband-to-baseband reciprocity. Thus, it enables the link adaptation using the uplink channel state information. Furthermore, preliminary hardware implementations of the relative calibration running on a real-time system show accurate results.

Heterogeneous Backhaul for Cloud-Based Mobile Networks

To meet the increasing capacity demands of future mobile networks, dense deployment of radio access nodes in combination with partly centralized processing by means of a cloud-based architecture is a promising option. In such an architecture, the design and optimization of the backhaul plays a crucial role. In this paper, we review different backhaul technologies available and discuss their characteristics for use in cloud-based networks. We point out how a heterogeneous backhaul network and a flexible centralization enables the proposed architecture and give an outlook on how a joint design of access and backhaul can help in meeting the increased demands.