Topology Control, Scheduling, and Spectrum Sensing in 5G Networks

The proliferation of intelligent wireless devices is remarkable. To address phenomenal traffic growth, a key objective of next-generation wireless networks such as 5G is to provide significantly larger bandwidth. To this end, the millimeter wave (mmWave) band (20 GHz -300 GHz) has been identified as a promising candidate for 5G and WiFi networks to support user data rates of multi-gigabits per second. However, path loss at mmWave is significantly higher than today\u27s cellular bands. Fortunately, this higher path loss can be compensated through the antenna beamforming technique-a transmitter focuses a signal towards a specific direction to achieve high signal gain at the receiver. In the beamforming mmWave network, two fundamental challenges are network topology control and user association and scheduling. This dissertation proposes solutions to address these two challenges. We also study a spectrum sensing scheme which is important for spectrum sharing in next-generation wireless networks. Due to beamforming, the network topology control in mmWave networks, i.e., how to determine the number of beams for each base station and the beam coverage, is a great challenge. We present a novel framework to solve this problem, termed Beamforming Oriented tOpology coNtrol (BOON). The objective is to reduce total downlink transmit power of base stations in order to provide coverage of all users with a minimum quality of service. BOON smartly groups nearby user equipment into clusters to dramatically reduce interference between beams and base stations so that we can significantly reduce transmit power from the base station. We have found that on average BOON uses only 10%, 32%, and 25% transmit power of three state-of-the-art schemes in the literature. Another fundamental problem in the mmWave network is the user association and traffic scheduling, i.e., associating users to base stations, and scheduling transmission of user traffic over time slots. This is because base station has a limited power budget and users have very diverse traffic, and also require some minimum quality of service. User association is challenging because it generally does not rely on the user distance to surrounding base stations but depends on if a user is covered by a beam. We develop a novel framework for user association and scheduling in multi-base station mmWave networks, termed the clustering Based dOwnlink user assOciation Scheduling, beamforming with power allocaTion (BOOST). The objective is to reduce the downlink network transmission time of all users\u27 traffic. On average, BOOST reduces the transmission time by 37%, 30%, and 26% compared with the three state-of-the-art user scheduling schemes in the literature. At last, we present a wavelet transform based spectrum sensing scheme that can simultaneously sense multiple subbands, even without knowing how the subbands are divided, i.e., their boundaries. It can adaptively detect all active subband signals and, thus, discover the residual spectrum that can be used by unlicensed devices

Neural Network Based Robust Adaptive Beamforming for Smart Antenna System

As the growing demand for mobile communications is constantly increasing, the need for better coverage, improved capacity, and higher transmission quality rises. Thus, a more efficient use of the radio spectrum is required. A smart antenna system is capable of efficiently utilizing the radio spectrum and is a promise for an effective solution to the present wireless system problems while achieving reliable and robust high-speed, high-data-rate transmission. Smart antenna technology offer significantly improved solution to reduce interference level and improve system capacity. With this technology, each user’s signal is transmitted and received by the base station only in the direction of that particular user. Smart antenna technology attempts to address this problem via advanced signal processing technology called beamforming. The adaptive algorithm used in the signal processing has a profound effect on the performance of a Smart Antenna system that is known to have resolution and interference rejection capability when array steering vector is precisely known. Adaptive beamforming is used for enhancing a desired signal while suppressing noise and interference at the output of an array of sensors. However the performance degradation of adaptive beamforming may become more pronounced than in an ideal case because some of underlying assumptions on environment, sources or sensor array can be violated and this may cause mismatch. There are several efficient approaches that provide an improved robustness against mismatch as like LSMI algorithm. Neural network is a massively parallel distributed processor made up of simple processing units, which has a natural propensity for storing experimental knowledge and making it available for use. Neural network methods possess such advantages as general purpose nature, nonlinear property, passive parallelism, adaptive learning capability, generalization capability and fast convergence rates. Motivated by these inherent advantages of the neural network, in this thesis work, a robust adaptive beamforming algorithm using neural network is investigated which is effective in case of signal steering vector mismatch. This technique employs a three-layer radial basis function neural network (RBFNN), which treats the problem of computing the weights of an adaptive array antenna as a mapping problem. The robust adaptive beamforming algorithm using RBFNN, provides excellent robustness to signal steering vector mismatches, enhances the array system performance under non ideal conditions and makes the mean output array SINR (Signal-to-Interference-plus- Noise Ratio) consistently close to the optimal one

On the Performance of Multi-Antenna Techniques for Spatially and Temporally Correlated Wireless Channels

As the demand for advanced wireless services continues to grow, system designers must employ innovative signal processing techniques to increase data throughput and maintain reliablity under adverse channel conditions. Multi-antenna techniques, such as space-time coding and beamforming, have shown promise in realizing these goals. As these and other techniques are introduced, understanding their performance in realistic scattering environments is of paramount importance. This thesis contributes to the field of wireless communications by determining the performance of multi-antenna techniques for spatially and temporally correlated wireless channels. First, we propose a general space-time covariance model that is applicable to arbitrary scatterer geometry, arbitrary array geometry at the base station and the mobile, and includes Doppler effects due to mobile motion. We then apply this model, in conjunction with a two-dimensional Gaussian scatterer model based on recent field measurements, to evaluate the exact pairwise error probability for arbitrary space-time block codes and determine an upper bound on the probability of a block error. In addition, we derive exact closed-form expressions for the symbol error probability for orthogonal space-time block coding, maximum ratio transmission, and beamsteering for spatially correlated quasi-static wireless channels. Finally, we present extensive numerical results that illustrate the performance of these techniques for varying degrees of spatial and temporal correlation. We also provide a comparative performance assessment of beamforming and orthogonal space-time block coding and determine the channel conditions for which one technique is favored over the other

Mismatched Processing for Radar Interference Cancellation

Matched processing is a fundamental filtering operation within radar signal processing to estimate scattering in the radar scene based on the transmit signal. Although matched processing maximizes the signal-to-noise ratio (SNR), the filtering operation is ineffective when interference is captured in the receive measurement. Adaptive interference mitigation combined with matched processing has proven to mitigate interference and estimate the radar scene. A known caveat of matched processing is the resulting sidelobes that may mask other scatterers. The sidelobes can be efficiently addressed by windowing but this approach also comes with limited suppression capabilities, loss in resolution, and loss in SNR. The recent emergence of mismatch processing has shown to optimally reduce sidelobes while maintaining nominal resolution and signal estimation performance. Throughout this work, re-iterative minimum-mean square error (RMMSE) adaptive and least-squares (LS) optimal mismatch processing are proposed for enhanced signal estimation in unison with adaptive interference mitigation for various radar applications including random pulse repetition interval (PRI) staggering pulse-Doppler radar, airborne ground moving target indication, and radar & communication spectrum sharing. Mismatch processing and adaptive interference cancellation each can be computationally complex for practical implementation. Sub-optimal RMMSE and LS approaches are also introduced to address computational limitations. The efficacy of these algorithms is presented using various high-fidelity Monte Carlo simulations and open-air experimental datasets

Keilaavan millimetriaaltoradiolinkin suuntaaminen ja seuraaminen

In order to provide high-throughput mobile broadband in a dense urban information society, upcoming cellular networks will finally employ the under-utilized millimeter-wave (mmW) frequencies. The challenging mmW radio environment, however, necessitates massive cell densification with wireless backhauling using very directional links. This thesis investigates how these links between access points may be aligned efficiently, and how alignment reflects the network organization. The work provides a thorough presentation of different high-level aspects and background information required when designing a mmW small cell system. In terms of alignment functionality, both automatic link establishment and proactive tracking are considered. Additionally, the presentation includes an overview of beam steerable antennas, mmW propagation in urban environments, and network organization. The thesis further specifies requirements, proposes possible approaches and compares those with existing implementations. Most of existing mmW beam alignment solutions are intended for short-range indoor communications and do not address the issues in cellular systems. While existing functionality considers only a single link between two devices, efficient design should consider both the entire network and the underlying phenomena. The devices should further exploit the existing network infrastructure, location and orientation information, and the concepts of machine learning. Even though the world has recently seen advancements in the related fields, there is still much work to be done before commercial deployment is possible.Seuraavan sukupolven matkaviestinjärjestelmien erittäin nopeissa datayhteyksissä tullaan hyödyntämään millimetriaaltoteknologiaa. Näillä taajuuksilla radioympäristö on kuitenkin hyvin haastava, mikä edellyttää verkon solutiheyden moninkertaistamista, täysin langattomia tukiasemia ja erittäin suuntaavia antenneja. Tässä diplomityössä tutkitaan eri keinoja kuinka tukiasemien väliset linkit kohdistetaan tehokkaasti, ja miten se vaikuttaa verkon rakenteeseen ja hallintaan. Työ tarjoaa kattavan taustaselvityksen mm-aaltosoluverkon toteuttamiseen tarvittavista asioista. Keilanohjausta tarkastellaan sekä verkon automaattisen laajentamisen että kohteen aktiivisen seurauksen kannalta. Tämän lisäksi työssä tutkitaan keilattavia antenneja, mm-aaltojen etenemistä kaupunkiympäristöissä ja verkkorakennetta. Näiden lisäksi työssä rajataan edellytykset, esitetään mahdollisia ratkaisuja, ja vertaillaan näitä olemassa oleviin toteutuksiin. Nykyiset keilaustoteutukset ovat pääasiassa suunniteltu lyhyen kantaman sisäyhteyksille, eivätkä siten vastaa ongelman asettelua. Aikaisempi toiminnallisuus keskittyy yhteen ainoaan linkkiin vaikka tehokas toteutus huomioisi koko järjestelmän kohdistusongelman fysikaalista perustaa unohtamatta. Verkkolaitteiden tulisi hyödyntää olemassa olevaa radioverkkoa, sekä paikka- että suuntatietoja, ja koneoppimisen keinoja. Vaikka aiheeseen liittyvä teknologia on kehittynyt viime vuosina harppauksin, mm-aaltosoluverkot ovat kaikkea muuta kuin valmiita markkinoille

Non-Radiative Calibration of Active Antenna Arrays

Antenna arrays offer significant benefits for modern wireless communication systems but they remain difficult and expensive to produce. One of the impediments of utilising them is to maintain knowledge of the precise amplitude and phase relationships between the elements of the array, which are sensitive to errors particularly when each element of the array is connected to its own transceiver. These errors arise from multiple sources such as manufacturing errors, mutual coupling between the elements, thermal effects, component aging and element location errors. The calibration problem of antenna arrays is primarily the identification of the amplitude and phase mismatch, and then using this information for correction. This thesis will present a novel measurement-based calibration approach, which uses a fixed structure allowing each element of the array to be measured. The measurement structure is based around multiple sensors, which are interleaved with the elements of the array to provide a scalable structure that provides multiple measurement paths to almost all of the elements of the array. This structure is utilised by comparison based calibration algorithms, so that each element of the array can be calibrated while mitigating the impact of the additional measurement hardware on the calibration accuracy. The calibration was proven in the investigation of the experimental test-bed, which represented a typical telecommunications basestation. Calibration accuracies of ±0.5dB and 5o were achieved for all but one amplitude outlier of 0.55dB. The performance is only limited by the quality of the coupler design. This calibration approach has also been demonstrated for wideband signal calibration