Johan Söder

Refined Statistical Analysis of Evolution Approaches for Wireless Networks

To meet future traffic and data rate demands, operators have the opportunity to select between a variety of network evolution approaches. This paper presents a new method for evaluating such approaches, in a simple yet operator specific way. The novelty of the method lies in that, with limited complexity, it takes into account not only conventional dimensioning parameters like targeted user experience, average traffic demand, user density and cell sizes, but also three dimensional spatial user and traffic distribution, site specific propagation, and deployment strategies. This is enabled through the use of an explicit city model, capturing the main characteristics of the operators environment. Applying the method to two examples of different cities illustrates the influence of the refinement parameters and their impact on the benefits of two evolution approaches: macro densification and deployment of small cells.

On the Capacity of the Wiener Phase-Noise Channel: Bounds and Capacity Achieving Distributions

In this paper, the capacity of the additive white Gaussian noise (AWGN) channel, affected by time-varying Wiener phase noise is investigated. Tight upper and lower bounds on the capacity of this channel are developed. The upper bound is obtained by using the duality approach, and by considering a specific distribution over the output of the channel. In order to lower-bound the capacity, first a family of capacity-achieving input distributions is found by solving a functional optimization of the channel mutual information. Then, lower bounds on the capacity are obtained by drawing samples from the proposed distributions through Monte Carlo simulations. The proposed capacity-achieving input distributions are circularly symmetric, non-Gaussian, and the input amplitudes are correlated over time. The evaluated capacity bounds are tight for a wide range of signal-to-noise-ratio (SNR) values, and thus they can be used to quantify the capacity. Specifically, the bounds follow the well-known AWGN capacity curve at low SNR, while at high SNR, they coincide with the high-SNR capacity result available in the literature for the phase-noise channel.

Refined evaluation of wireless network evolution approaches

Operators need to continuously evolve their networks to meet future traffic and data rate demands. Today there is a wide selection of network evolution approaches to choose from. This paper uses a novel evaluation method to evaluate some of those approaches in a simple yet operator specific way. The method takes into account not only conventional dimensioning parameters like targeted user experience, average traffic demand, user density and cell sizes, but also three dimensional spatial user and traffic distribution, site specific propagation, and deployment strategies. It is shown that by applying this method to a low-rise urban scenario the potential capacity gains of higher order sectorization, additional spectrum, and site densification can be predicted. For densification with different node types, such as macro, micro and pico nodes, the respective site counts needed to reach a given performance target can be obtained and compared. Furthermore a comparison of the capacity increase per added low power node shows that there are diminishing returns in a high-rise scenario, but not in a low-rise scenario.

Analysis of the potential for increased spectral reuse in wireless LAN

By allowing simultaneous transmissions in neighbouring cells the spectral reuse and the overall throughput of a WLAN system can be increased. We have investigated the impact of varying the clear channel assessment threshold (CCAT) in different network deployments defined by IEEE 802.11ax Task Group, and we show the potential of 4 different algorithms. By increasing the CCAT value from todays legacy value of -82 dBm to -62 dBm, an increase of up to 23% in the mean user throughput is observed. Further improvements are observed by using more advanced algorithms such as dynamic sensitivity control (DSC). The performance is also compared to those of reuse 1 systems and systems with uplink-downlink separation.