David Grace

Optimizing an array of antennas for cellular coverage from a high altitude platform

In a wireless communications network served by a high altitude platform (HAP) the cochannel interference is a function of the antenna beamwidth, angular separation and sidelobe level. At the millimeter wave frequencies proposed for HAPs, an array of aperture type antennas on the platform is a practicable solution for serving the cells. We present a method for predicting cochannel interference based on curve-fit approximations for radiation patterns of elliptic beams which illuminate cell edges with optimum power, and a means of estimating optimum beamwidths for each cell of a regular hexagonal layout. The method is then applied to a 121 cell architecture. Where sidelobes are modeled as a flat floor at 40-dB below peak directivity, a cell cluster size of four yields carrier-to-interference ratios (CIRs), which vary from 15 dB at cell edges to 27 dB at cell centers. On adopting a cluster size of seven, these figures increase, respectively, to 19 and 30 dB. On reducing the sidelobe level, the improvement in CIR can be quantified. The method also readily allows for regions of overlapping channel coverage to be shown.

Improving the system capacity of broadband services using multiple high-altitude platforms

A method of significantly improving the capacity of high-altitude platform (HAP) communications networks operating in the millimeter-wave bands is presented. It is shown how constellations of HAPs can share a common frequency allocation by exploiting the directionality of the user antenna. The system capacity of such constellations is critically affected by the minimum angular separation of the HAPs and the sidelobe level of the user antenna. For typical antenna beamwidths of approximately 5/spl deg/ an inter-HAP spacing of 4 km is sufficient to deliver optimum performance. The aggregate bandwidth efficiency is evaluated, both theoretically using the Shannon equation, and using practical modulation and coding schemes, for multiple HAP configurations delivering either single or multiple cells. For the user antenna beamwidths used, it is shown that capacity increases are commensurate with the increase in the number of platforms, up to 10 HAPs. For increases beyond this the choice of constellation strategy becomes increasingly important.

Using cognitive radio to deliver ‘Green’ communications

This paper discusses different ways of delivering ‘green’ cognitive radio based systems. Fundamental is the need to exploit the free spectrum available and power efficient modulation where possible. The paper describes a variable power/bandwidth efficient modulation strategy where the modulation level is adjusted by cognitively determining the assignment and use of the available spectrum, taking into account the channel occupancy probability. Battery life for different techniques is also considered. Secondly, the paper discusses ways to reduce the complexity overall of cognitive radio systems, particularly in the need for spectrum sensing by exploiting distributed artificial intelligence. Techniques presented show how it is possible to largely eliminate the need for spectrum sensing, along with the associated energy consumption, by using reinforcement learning to develop a preferred channel set in each device. Finally, the paper discusses the potential benefits of the use of antenna directionality to improve energy efficiency, and the associated problems that still must be solved before this technique can deliver ‘green’ radio.

Integrating users into the wider broadband network via high altitude platforms

An overview of CAPANINA, a project funded by the European Commissions 6th Framework Programme, is presented. The project is developing communications technologies for use with aerial platforms with the aim of integrating users in hard to reach areas and those disadvantaged by geography into the wider broadband network. The article discusses the three broad areas of the project. Specific aspects covered include broadband applications and services selection, along with appropriate integrated delivery configurations to deliver the required capacity and upgradeability; and the associated trials, along with the required wireless and free space optical equipment. Longer-term research underway into delivering broadband backhaul to high-speed trains from aerial platforms, enabling integration with onboard WLAN access points, is also discussed.

Providing multimedia communications services from high altitude platforms

System level design considerations for high altitude platforms operating in the mm-wave bands are examined. Propagation effects in these bands are outlined, followed by a brief introduction to different platform scenarios. Ground-based and platform-based fixed wireless access scenarios are considered, and it is shown that using a platform, a single base station can supply a much larger coverage area than a terrestrial base station. The effects on performance of platform displacement from its desired location with both fixed and steerable antennas are also examined. It is shown that steerable antennas are of most use when fixed stations are immediately below the platform, with no benefit for fixed stations on the edge of coverage. The bandwidths required to serve several traffic distributions (suburbs and city centre based) are evaluated using the Shannon equation. It is shown that capacity can be constrained when users are located in the city centres, despite longer line of sight paths to users out in the suburbs. The effects of temporal changes in the spatial traffic distribution are investigated. It is shown that bandwith requirements can be reduced if the platform moves to track these changes. Copyright

Efficient exploration in reinforcement learning-based cognitive radio spectrum sharing

This study introduces two novel approaches, pre-partitioning and weight-driven exploration, to enable an efficient learning process in the context of cognitive radio. Learning efficiency is crucial when applying reinforcement learning to cognitive radio since cognitive radio users will cause a higher level of disturbance in the exploration phase. Careful control of the tradeoff between exploration and exploitation for a learning-enabled cognitive radio in order to efficiently learn from the interactions with a dynamic radio environment is investigated. In the pre-partitioning scheme, the potential action space of cognitive radios is reduced by initially randomly partitioning the spectrum in each cognitive radio. Cognitive radios are therefore able to finish their exploration stage faster than more basic reinforcement learning-based schemes. In the weight-driven exploration scheme, exploitation is merged into exploration by taking into account the knowledge gained in exploration to influence action selection, thereby achieving a more efficient exploration phase. The learning efficiency in a cognitive radio scenario is defined and the learning efficiency of the proposed schemes is investigated. The simulation results show that the exploration of cognitive radio is more efficient by using pre-partitioning and weight-driven exploration and the system performance is improved accordingly.

Integration of a HAP within a Terrestrial UMTS Network: InterferenceAnalysis and Cell Dimensioning

In this paper we consider several issues regarding the use of a High Altitude Platform (HAP) as a mobile communications base station for the UMTS standard. We refer in particular to a solar powered unmanned stratospheric platform named Heliplat, which is currently being designed at Politecnico di Torino within the HeliNet project funded by the European Community as part of the Fifth Framework Programme. Here we present a feasibility study of the use of the Heliplat platform as a UMTS base station within anintegrated terrestrial-stratospheric UMTS cellular system. We take into account the power consumption and the weight constraint imposed by the platform technology, the interference required for a proper system operation and the requirement of maintaining full compatibility with the UMTS standard.

LMDS from high altitude aeronautical platforms

System level design considerations for high altitude aeronautical platforms operating in the LMDS band are examined. Propagation effects in the LMDS band are outlined, followed by a brief introduction to different platform scenarios. Ground-based and platform-based fixed wireless access scenarios are considered, and it is shown that using a platform, considerably longer link lengths can be used. The effects on performance of platform displacement from its desired location with both fixed and steerable antennas are also examined. It is shown that steerable antennas are of most use when fixed stations are immediately below the platform, with no benefit for fixed stations on the edge of coverage.

Reducing call dropping in distributed dynamic channel assignment algorithms by incorporating power control in wireless ad hoc networks

Methods of substantially reducing call dropping in networks which use distributed dynamic channel assignment (DDCA) schemes are discussed. Interference and received power thresholds coupled with power control are used to maintain performance, without the need for intra-cell handoffs. It is shown that the schemes reduce call dropping and increase capacity compared to those using fixed transmitter power. The schemes are developed with the aid of mathematical analysis and a pictorial model. Results are presented which show that call dropping may be virtually eliminated in shadowing environments with the median transmitter power being reduced by 15 dB. The various call dropping mechanisms are discussed, and it is suggested that the residual level of call dropping is principally a result of multiple additional call arrivals close to an active link. Methods to make further reductions in the call dropping probability are also proposed.

Two-stage reinforcement-learning-based cognitive radio with exploration control

This study presents a novel two-stage reinforcement-learning-based algorithm for distributed cognitive radio (CR) spectrum sharing. The traditional reinforcement-learning model is modified in order to be applied in a fully distributed CR scenario. CRs are able to discover the best available resources autonomously by utilising learning, which results in significantly improved performance, while reducing the need for spectrum sensing. Instead of sensing all available spectrum arbitrarily, the scheme is designed to share the spectrum based on an optimal spectrum sharing strategy, which is discovered by the CR agents from their trial-and-error interactions with the wireless communication environment. On the other hand, the inherent exploration against exploitation trade-off seen in reinforcement learning is also examined in the context of CR. A ‘warm-up’ stage is proposed to effectively control the exploration phase of the learning process. A better system performance can be expected by carefully balancing the tradeoff between exploration and exploitation. The benefit of applying a warm-up stage is demonstrated. Comparisons of system performance using different warm-up strategies are also given to illustrate their impact on the spectrum sharing process.