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Fixed WiMAX Field Trial Measurements and Analyses

Much hype is spread about the performance of WiMAX, and many contrary statements are put forward. A reason for the confusion is that little or no published material exists about WiMAX performance based on measurements in real life field trials. We therefore set up a test-bed using WiMAX equipment now on the marked, and did extensive, real life field trial measurements. This paper presents measured throughput and received signal strength under conditions typical for fixed WiMAX systems. Based on the results, throughput is analyzed and analytical expressions representing the measurements are derived for easy use in models.

Evaluation of business cases for a cognitive radio network based on wireless sensor network

This paper proposes and evaluates three business case scenarios for deployment of a sensor network aided cognitive radio system in a typical European city. The first and main business case is based on spectrum sharing, where several spectrum owners establish a joint venture and this joint venture gets the rights to use the “unused” spectrum resources of all those spectrum owners in a cognitive way. Then we study the business case of a spectrum broker, an entity that deploys, builds and operates a sensor network and sells either sensing information or information on spectrum opportunities to one or more cognitive radio operators. Finally we analyze the potential of a new entrant without existing infrastructure or frequency licenses, that uses a sensor network aided cognitive radio system to offer a nomadic mobile broadband service. It is found that the spectrum sharing business case is one of the best possible cases for the studied system because the joint venture operator has free access to frequency resources of the mother companies, detailed knowledge of the primary systems and good possibilities for sharing infrastructure with the owning operators. However, since the studied system is an innovative concept and some of the assumed parameters are therefore uncertain, it should be noted that the main value of the business case calculations is to identify critical aspects influencing the profitability so that future research and development work can focus on them. It is found that the most critical aspects are the fixed sensor density, the fixed sensor operational costs and the number of new cognitive base station sites required.

Benefits of Self-Organizing Networks (SON) for Mobile Operators

Self-Organizing Networks (SON) is a collection of functions for automatic configuration, optimization, diagnostisation and healing of cellular networks. It is considered to be a necessity in future mobile networks and operations due to the increased cost pressure. The main drivers are essentially to reduce CAPEX and OPEX, which would otherwise increase dramatically due to increased number of network parameters that has to be monitored and set, the rapidly increasing numbers of base stations in the network and parallel operation of 2G, 3G and Evolved Packet Core (EPC) infrastructures. This paper presents evaluations on the use of some of the most important SON components. Mobile networks are getting more complex to configure, optimize and maintain. Many SON functions will give cost savings and performance benefits from the very beginning of a network deployment and these should be prioritized now. But even if many functions are already available and can give large benefits, the field is still in its infancy and more advanced functions are either not yet implemented or have immature implementations. It is therefore necessary to have a strategy for how and when different SON functions should be introduced in mobile networks.

Business case proposal for a cognitive radio network based on Wireless Sensor Network

This paper describes a business case scenario and gives the results of a business case analysis for deployment of a sensor network aided cognitive radio system in a typical European city. The main idea behind the business case is that several spectrum owners will establish a joint venture and this joint venture will get the right to use the “unused” spectrum resources of all the companies in a cognitive way. The joint venture will base its operation on a Wireless Sensor Network aided Cognitive Radio concept, which means that a network of fixed sensors is deployed in order to improve the systems capabilities for detecting primary users and spectrum holes. The main value of the business case calculation is to identify critical aspects influencing the profitability so that future research and development work can focus on them. It is found that the most critical aspects are the fixed sensor density, the fixed sensor operational costs and the number of new cognitive base station sites required.

Mapping Cognitive Radio System Scenarios into the TVWS Context

Cognitive Radio has been one of the key research topics in the wireless community for about 10xa0years. The digital switch-over in the TV bands provides opportunities for Cognitive Radio Systems (CRS) to operate in the 470–790xa0MHz spectrum under incumbent protection restrictions. Locally unused spectrum in this band is often referred to as TV whitespace (TVWS). Regulatory bodies, in particular the US Federal Communications Commission (FCC) and Ofcom in the UK, have specified parameters under which CRS shall operate. In this paper we analyse key scenarios for CRS stemming from the QoSMOS project. We then analyse how these scenarios can be mapped into the TV whitespace (TVWS) context by considering link budget computation based on FCC and Ofcom transmit power recommendations plus statistical propagation models for the UHF band. We also consider the expected capacity which can be achieved when using TVWS as a capacity extension in an LTE network. We also show how cognitive femtocells can be used to provide outdoor coverage when deployment is based on random location. We eventually conclude on the most promising scenarios in the context of the TVWS usage.

Scheduling Policies in Time and Frequency Domains for LTE Downlink Channel: A Performance Comparison

A key feature of the Long-Term Evolution (LTE) system is that the packet scheduler can make use of the channel quality information (CQI), which is periodically reported by user equipment either in an aggregate form for the whole downlink channel or distinguished for each available subchannel. This mechanism allows for wide discretion in resource allocation, thus promoting the flourishing of several scheduling algorithms, with different purposes. It is therefore of great interest to compare the performance of such algorithms under different scenarios. Here, we carry out a thorough performance analysis of different scheduling algorithms for saturated User Datagram Protocol (UDP) and Transmission Control Protocol (TCP) traffic sources, as well as consider both the time- and frequency-domain versions of the schedulers and for both flat and frequency-selective channels. The analysis makes it possible to appreciate the difference among the scheduling algorithms and to assess the performance gain, in terms of cell capacity, users fairness, and packet service time, obtained by exploiting the richer, but heavier, information carried by subchannel CQI. An important part of this analysis is a throughput guarantee scheduler, which we propose in this paper. The analysis reveals that the proposed scheduler provides a good tradeoff between cell capacity and fairness both for TCP and UDP traffic sources.

A performance comparison of LTE downlink scheduling algorithms in time and frequency domains

A number of scheduling algorithms for LTE downlink have been proposed and evaluated leveraging the flexibility of the resource allocation in both the time and the frequency domain. However, the existing literature falls short when it comes to schedulers that provide throughput guarantees. In this paper, we contribute to fill this gap by implementing a scheduling algorithm that provides long-term throughput guarantees to the different users, while opportunistically exploiting the instantaneous channel fluctuations to increase the cell capacity. We perform a thorough performance analysis comparing this algorithm with the other well known algorithms by means of extensive ns-3 simulations, both for saturated UDP and TCP traffic sources. The analysis makes it possible to appreciate the difference among the scheduling algorithms, and to assess the performance gain, both in terms of cell capacity and packet service time, obtained by allowing the schedulers to work in the frequency domain.

Performance of a Sensor Network Aided Cognitive Radio system

A Sensor Network Aided Cognitive Radio Network uses the concept of a wireless sensor network that assists a cognitive radio network by providing information about the current primary spectrum occupancy. In this paper we study the performance of the cognitive network for various cell sizes and transmit power levels when deployed co-located with a mobile primary system that uses a cellular reuse pattern with seven frequencies. Co-location of secondary and primary base stations has been found to be very important in order to reduce network costs. An expression for the degree of co-location of secondary and primary base stations is derived and used for identifying optimal secondary cell sizes. For these optimal secondary cell sizes, we determine the performance in terms of throughput, packet loss, delay, coverage and connectivity when using spectrum holes in the space, time and frequency domains. Especially, we find that cell size and transmit power levels are crucial for secondary system performance, and that smaller cell sizes and less expensive base stations for the secondary system such as WiFi access points and femto-cells is beneficial.

On planning small cell backhaul networks

Small cells are expected to play an important role in future mobile networks to meet the rapidly increasing capacity demand. However, this requires that cost efficient backhaul solutions are found. This is a very challenging task given the large number of small cells that must be connected. In this paper we propose a set of practical methods that mobile operators can use as tools when planning small cell backhaul networks. The tools can help operators find the best way to connect the base station nodes and which technology to use on each link. Two methods are proposed for planning fiber-only networks. Fiber only solutions are interesting since long term backhaul solutions are expected to be dominated by fiber links and can be used to find heuristic solutions to multi-technology problems by e.g. replacing some fiber links with radio links. Optimal fiber-only networks with a tree topology can be easily found by a minimum weight spanning tree algorithm. By introducing a new metric we show that more resilient ring topology based solutions can be found by solving a traveling salesman type of problem. For heterogeneous multi-technology backhaul networks we propose a Mixed Integer linear Programming (MIP) problem formulation that allows inclusion of a wide range of requirements and constraints. The solutions can be made robust against varying traffic conditions by specifying capacity demand for different scenarios and both point-to-point and point-to-multipoint type of technologies can be included in the optimization. To verify the methods an example case study is performed for a small city.

Comparison of inter-cell interference models for cellular networks

In this paper we compare some methods to analyze the influence inter-cell interference will have on coverage/outage probabilities in cellular OFDMA networks. The framework is based on a common method to find the Laplace transform of the interference from neighboring cells. It turns out that the analysis is highly simplified if the fading has a Suzuki probability distribution. The modeling approach allows for both fixed and stochastic locations of base stations, and the different models are applied to quantify the effect of the interference on the coverage/outage probabilities in LTE networks. We consider several scenarios ranging from fixed hexagonal layout of base station to stochastic distribution of base stations based on Poisson Point Processes. Numerical examples show quite large differences in coverage/outage probabilities for the network scenarios considered.