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MSc Thesis
Title: "Teletraffic Analysis of the Next-Generation Integrated Terrestrial/Satellite Mobile Radio Networks"   abstract   full-text pdf

PhD Thesis
Title: "Non-Linear Precoding and Equalisation for Broadband MIMO Channels"   abstract   full-text pdf

MSc Thesis Abstract

As mobile service demands increase dramatically, interest in cellular system structure with hierarchical terrestrial/satellite architecture has emerged. Without satellite participation, terrestrial cellular systems would be primarily restricted to regional service. For the network to have seamless radio coverage and sufficient capacity to accommodate anticipated high teletraffic demand, integration of satellite network and terrestrial cellular system is indispensable. In this research project, a space/terrestrial mobile radio communication network with multiple hierarchical cellular overlays is considered. In the lowest hierarchical level, microcells serve the highest teletraffic density, while overlaying macrocells serve both calls from areas that are difficult to be covered by microcells, as well as overflow traffic from microcells. At the highest hierarchical level, satellites focus their spotbeams to serve satellite-only users sparsely distributed and act as teletraffic relief for the terrestrial segment. At each hierarchical level different priority schemes are used to privilege handoff requests. Reserved channel scheme (RCS) is applied in the microcell layer, both RCS and sub-rating scheme (SRS) are used in the macrocell layer, while in the spotbeam cell layer, RCS, SRS, and queuing priority scheme (QPS) are implemented. An analytical teletraffic model is developed to evaluate the proposed architecture. Numerical results are presented and discussed for the new call blocking, handoff failure, forced termination and noncompletion probabilities. The work presented in the thesis will help understanding the next-generation communication network and thereby allow better engineering of its resources.



PhD Thesis Abstract

Multiple-input multiple-output (MIMO) technology promises significant capacity improvements in order to more efficiently utilise the radio frequency spectrum. To achieve its anticipated multiplexing gain as well as meet the requirements for high data rate services, proposed broadband systems are based on OFDM or similar block based techniques, which are afflicted by poor design freedom at low redundancy, and are known to suffer badly from co-channel interference (CCI) in the presence of synchronisation errors. Non-block based approaches are scarce and use mostly decision feedback equalisation (DFE) or V-BLAST approaches adopted for the broadband case, as well as Tomlinson-Harashima precoding (THP). These methods do not require a guard interval and can therefore potentially achieve a higher spectral efficiency. The drawback of these schemes is the large effort in determining the optimum detection order in both space and time, often motivating the adoption of suboptimal approaches.

In this thesis, we focus on non-block based precoding and equalisation schemes aiming to achieve higher data throughputs with improved bit error ratio (BER) compared to existing approaches. In order to achieve this, a recently developed broadband singular value decomposition (BSVD) technique is applied to decouple a broadband MIMO channel into independent frequency selective single-input single-output (SISO) subchannels of ordered qualities, thereby cancelling CCI. Secondly, these dispersive broadband SISO subchannels are individually equalised using non-linear DFE or THP schemes with a variable transmission rate that best matches the individual qualities of the respective subchannels, whereby the decision delay can be independently optimised for every subchannel. This method is benchmarked through simulations against a state-of-the-art broadband MIMO THP technique with optimised spatio-temporal ordering showing that improved BER performance can be achieved under the constraints of identical data throughput and transmit power.

In order to maximise the data throughput of our proposed method or similar multichannel systems, adaptive bit and power loading schemes have been applied. A rate-optimal approach known as a greedy algorithm is considered, whereby optimality is guaranteed by considering an appropriate bit allocation cost function and then iteratively assigning one bit at a time to the least cost-expensive subchannel. Constraining the transmit power budget and target BER of the overall transmission system, we propose a greedy power allocation (GPA) algorithm to optimise the achieved data throughput. While maximising data rate, the GPA algorithm can also save some unused power from the total transmit budget. This power is further utilised to enhance the mean BER w.r.t. the constrained target through two proposed power redistribution algorithms.

It is well known that the GPA algorithm is computationally very expensive due to the iterative nature of the algorithm. In order to efficiently reduce the computational complexity of the GPA algorithm, suboptimal GPA schemes are proposed by considering a subchannel grouping concept. We show by numerical results that these schemes, while hardly sacrificing any performance compared to the original GPA algorithm, can significantly reduce the computational complexity by an order of magnitude.