Ingo Viering

A Mathematical Perspective of Self-Optimizing Wireless Networks

We present a mathematical framework for quantitative investigations of self-optimizing wireless networks (SON) with focus on the 3GPP Long-Term Evaluation (LTE) system. Basic target functions, such as the signal-to-noise ratio distribution, the number of satisfied users, or energy efficiency are derived as a figure of merit, including the impact of adaptation of downlink transmit power adaptation, antenna tilt, and the handover parameter. The framework is exemplified by basic investigations on load balancing.

Short-term and long-term diagonalization of correlated MIMO channels with adaptive modulation

Theoretical results on MIMO capacity maximization suggest the decoupling of the MIMO channel into independent subchannels with optimum water-filling on these subchannels. Those results inspire the development of real systems that diagonalize the MIMO channel and adaptively control the modulation on each of the resulting subchannels. We study the design of a fully adaptive transmitter, where transmit filtering and adaptive modulation is controlled by short-term as well as long-term channel state information (channel correlation), where the focus is on channels with correlated fading at transmitter and receiver array. To this end, we are motivating the use of long-term channel eigenmodes by capacity-independent considerations. Simulation results confirm the potential of fully adaptive transmit processing.

Optimizing the Radio Network Parameters of the Long Term Evolution System Using Taguchi's Method

One of the primary aims of radio network planning is to configure the parameters of the base stations such that the deployment achieves the required quality of service. However, the adjustment of radio network parameters in a heterogeneous macro-only cellular network is a complex task, which involves a large number of configuration parameters with interactions among them. Existing commercial planning tools are based on local search methods, e.g., simulated annealing, that require problem-specific and heuristic definitions of the input parameters. The problem with local search methods is that their performance can significantly be degraded if the input parameters are misconfigured. To overcome these difficulties, an iterative optimization procedure based on Taguchis method is proposed to find near-optimal settings. Taguchis method was originally applied in manufacturing processes and has recently been used in several engineering fields. Unlike local search methods that heuristically discover the multidimensional parameter space of candidate solutions, Taguchis method offers a scientifically disciplined methodology to explore the search space and select near-optimal values for the parameters. In this paper, the application of Taguchis method in radio network optimization is illustrated by setting typical radio network parameters of the Long Term Evolution (LTE) system, i.e., the uplink power control parameters, antenna tilts, and azimuth orientations of trisectored macro base stations. Simulation results reveal that Taguchis method is a promising approach for radio network optimization with respect to performance and computational complexity. It is shown that Taguchis method has a comparable performance to simulated annealing in terms of power control and antenna azimuth optimizations; however, it performs better in terms of antenna tilt optimization. Moreover, it is presented that the performance of simulated annealing, as opposed to Taguchis method, highly depends on the definition of the input parameters.

On Uplink Intercell Interference in a Cellular System

A new semi-analytical method to analyze intercell interference in a cellular system is introduced. A sound comprehension of the properties of intercell interference is the key to a meaningful assessment of communication systems without exhaustive simulation campaigns. We consider the basic access schemes TDMA, WCDMA and random OFDMA for uplink transmission. We will also give hints, how the methods can be extended to capture other access schemes, and/or additional features. The focus of this work is more on the introduction of the new methodology. In principle, we describe the intercell interference as a random variable which is composed of many other random variables. The distributions, and in particular the mutual dependencies of those have to be carefully studied. Applications and extensions of the ideas will be addressed in future work, only first examples are given here.

Small-Cell Self-Organizing Wireless Networks

Increasing the spatial reuse of frequency spectrum by deploying more access points has historically been the most effective means to improve the capacity of any cellular communication network. Todays mobile networks face a proliferation of data services and overall demand for data traffic that has been strongly increasing over several years. As a result, increasing network capacity through the deployment of small lower power nodes is of key importance for mobile network operators. Although such small access points are conceptually equivalent to conventional cellular base stations in many ways, the expected large number of small cells as well as their much more dynamic unplanned deployment raise a variety of challenges in the area of network management. This paper discusses such challenges and reviews state-of-the-art modeling as well as selected network management techniques.

Challenges in mobile network operation: Towards self-optimizing networks

This paper reviews current status and trends in the application of self-organizing principles to advanced wireless networks, such as 3GPP Long-term Evolution (LTE). The transfer of research results and concepts to real-world networks imposes additional constraints and requirements, which open a multitude of interesting new fields for applied research. Particular challenges include defining appropriate assessment criteria, evaluation methodology, as well as a variety of interrelations between use cases with conflicting goals and mutual parameter dependencies yielding non-closed-form problems. Furthermore only partial, error-prone and potentially inconsistent information is available. Additional challenges include minimization of overhead, stability, and convergence issues, in particular for decentralized solutions.

A game-theoretic approach to load balancing in cellular radio networks

Game theory provides an adequate methodology for analyzing topics in communication systems that include trade-offs such as the subject of load balancing. As a means of balancing the load in the network, users are handed over from highly loaded cells to lower loaded neighbors increasing the capacity usage and the Quality of Service (QoS). The algorithm that calculates the amount of the load that each cell should decide either to accept or to offload might differ if the base stations are from distinct vendors, which in-turn may have an impact on the performance of the network. In this paper, we study the load balancing problem using a game-theoretic approach where, in the worst case, each cell decides independently on the amount of load that maximizes its payoff in an uncoordinated way and investigate whether the resulting Nash equilibrium would exhaust the gains achieved. Moreover, we alter the behavior of the players using the linear pricing technique to have a more desirable equilibrium. The simulation results for the Long Term Evolution (LTE) network have shown that the Nash equilibrium point can still provide a remarkable increase in the capacity when compared to a system without load balancing and has a slight degradation in performance with respect to the equilibrium achieved by linear pricing.

A closed-form bound on correlated MIMO channel capacity

The exact calculation of the ergodic MIMO channel capacity with channel correlation is mathematically at least very challenging. Having no closed-form analytical expression available for the capacity is making it difficult to derive optimum stochastic water-filling schemes that are based on long-term channel state information (channel correlation) only. We therefore derive a closed-form tight upper bound on the ergodic capacity of correlated MIMO channels. The bound takes into account both the effects of correlation at the transmitter as well as the receiver. Furthermore, we give a recursive algorithm for its efficient calculation. Simulations demonstrate the tightness of the bound and show that a long-term water-filling scheme based on the new bound yields almost the same performance as a scheme with full short-term (instantaneous) channel state information.

Joint optimization of radio parameters in HSDPA

In this paper we propose two contributions to the field of cross-layer optimization for third generation (3G) mobile communication systems. The first chapter derives an analytical bijective system model for the quality of service parameters throughput and delay in an HSDPA system. Link level simulations reveal an excellent match of the new model components. In the second part, the derived model is used to design a cross-layer optimization technique, serving a set of quality of service (QoS) demands with minimum necessary transmit power. The optimized system yields the same QoS performance with a significantly lower amount of transmit power, which in future investigations will enable scheduling algorithms to maximize the system capacity.

Mobility Modeling and Performance Evaluation of Multi-Connectivity in 5G Intra-Frequency Networks

Ultra-high reliable communication and improved capacity are some of the major requirements of the 5th generation (5G) mobile and wireless networks. Achieving the aforementioned requirements necessitates avoiding radio link failures and the service interruption that occurs during the failures and their re-establishment procedures. Moreover, the latency associated with packet forwarding in classical handover procedures should be resolved. This paper proposes a multi-connectivity concept for a cloud radio access network as a solution for mobility related link failures and throughput degradation of cell-edge users. The concept relies on the fact that the transmissions from co-operating cells are co-ordinated for both data and control signals. Latency incurred due to classical handover procedures will be inherently resolved in the proposed multi-connectivity scheme. Simulation results are shown for a stand alone ultra dense small cells that use the same carrier frequency. It is shown that the number of mobility failures can considerably be decreased without a loss in the throughput performance gain of cell-edge users.