Asymptotically-Optimal, Fast-Decodable, Full-Diversity STBCs

For a family/sequence of STBCs $\mathcal{C}_1,\mathcal{C}_2,\dots$, with increasing number of transmit antennas $N_i$, with rates $R_i$ complex symbols per channel use (cspcu), the asymptotic normalized rate is defined as $\lim_{i \to \infty}{\frac{R_i}{N_i}}$. A family of STBCs is said to be asymptotically-good if the asymptotic normalized rate is non-zero, i.e., when the rate scales as a non-zero fraction of the number of transmit antennas, and the family of STBCs is said to be asymptotically-optimal if the asymptotic normalized rate is 1, which is the maximum possible value. In this paper, we construct a new class of full-diversity STBCs that have the least ML decoding complexity among all known codes for any number of transmit antennas $N>1$ and rates $R>1$ cspcu. For a large set of $\left(R,N\right)$ pairs, the new codes have lower ML decoding complexity than the codes already available in the literature. Among the new codes, the class of full-rate codes ($R=N$) are asymptotically-optimal and fast-decodable, and for $N>5$ have lower ML decoding complexity than all other families of asymptotically-optimal, fast-decodable, full-diversity STBCs available in the literature. The construction of the new STBCs is facilitated by the following further contributions of this paper:(i) For $g > 1$, we construct $g$-group ML-decodable codes with rates greater than one cspcu. These codes are asymptotically-good too. For $g>2$, these are the first instances of $g$-group ML-decodable codes with rates greater than $1$ cspcu presented in the literature. (ii) We construct a new class of fast-group-decodable codes for all even number of transmit antennas and rates $1 < R \leq 5/4$.(iii) Given a design with full-rank linear dispersion matrices, we show that a full-diversity STBC can be constructed from this design by encoding the real symbols independently using only regular PAM constellations.Comment: 16 pages, 3 tables. The title has been changed.The class of asymptotically-good multigroup ML decodable codes has been extended to a broader class of number of antennas. New fast-group-decodable codes and asymptotically-optimal, fast-decodable codes have been include

Block-Orthogonal Space-Time Code Structure and Its Impact on QRDM Decoding Complexity Reduction

Full-rate space time codes (STC) with rate = number of transmit antennas have high multiplexing gain, but high decoding complexity even when decoded using reduced-complexity decoders such as sphere or QRDM decoders. In this paper, we introduce a new code property of STC called block-orthogonal property, which can be exploited by QR-decomposition-based decoders to achieve significant decoding complexity reduction without performance loss. We show that such complexity reduction principle can benefit the existing algebraic codes such as Perfect and DjABBA codes due to their inherent (but previously undiscovered) block-orthogonal property. In addition, we construct and optimize new full-rate BOSTC (Block-Orthogonal STC) that further maximize the QRDM complexity reduction potential. Simulation results of bit error rate (BER) performance against decoding complexity show that the new BOSTC outperforms all previously known codes as long as the QRDM decoder operates in reduced-complexity mode, and the code exhibits a desirable complexity saturation property.Comment: IEEE Journal of Selected Topics in Signal Processing, Vol. 5, No. 8, December 201

Quality-driven resource utilization methods for video streaming in wireless communication networks

This research is focused on the optimisation of resource utilisation in wireless mobile networks with the consideration of the users’ experienced quality of video streaming services. The study specifically considers the new generation of mobile communication networks, i.e. 4G-LTE, as the main research context. The background study provides an overview of the main properties of the relevant technologies investigated. These include video streaming protocols and networks, video service quality assessment methods, the infrastructure and related functionalities of LTE, and resource allocation algorithms in mobile communication systems. A mathematical model based on an objective and no-reference quality assessment metric for video streaming, namely Pause Intensity, is developed in this work for the evaluation of the continuity of streaming services. The analytical model is verified by extensive simulation and subjective testing on the joint impairment effects of the pause duration and pause frequency. Various types of the video contents and different levels of the impairments have been used in the process of validation tests. It has been shown that Pause Intensity is closely correlated with the subjective quality measurement in terms of the Mean Opinion Score and this correlation property is content independent. Based on the Pause Intensity metric, an optimised resource allocation approach is proposed for the given user requirements, communication system specifications and network performances. This approach concerns both system efficiency and fairness when establishing appropriate resource allocation algorithms, together with the consideration of the correlation between the required and allocated data rates per user. Pause Intensity plays a key role here, representing the required level of Quality of Experience (QoE) to ensure the best balance between system efficiency and fairness. The 3GPP Long Term Evolution (LTE) system is used as the main application environment where the proposed research framework is examined and the results are compared with existing scheduling methods on the achievable fairness, efficiency and correlation. Adaptive video streaming technologies are also investigated and combined with our initiatives on determining the distribution of QoE performance across the network. The resulting scheduling process is controlled through the prioritization of users by considering their perceived quality for the services received. Meanwhile, a trade-off between fairness and efficiency is maintained through an online adjustment of the scheduler’s parameters. Furthermore, Pause Intensity is applied to act as a regulator to realise the rate adaptation function during the end user’s playback of the adaptive streaming service. The adaptive rates under various channel conditions and the shape of the QoE distribution amongst the users for different scheduling policies have been demonstrated in the context of LTE. Finally, the work for interworking between mobile communication system at the macro-cell level and the different deployments of WiFi technologies throughout the macro-cell is presented. A QoEdriven approach is proposed to analyse the offloading mechanism of the user’s data (e.g. video traffic) while the new rate distribution algorithm reshapes the network capacity across the macrocell. The scheduling policy derived is used to regulate the performance of the resource allocation across the fair-efficient spectrum. The associated offloading mechanism can properly control the number of the users within the coverages of the macro-cell base station and each of the WiFi access points involved. The performance of the non-seamless and user-controlled mobile traffic offloading (through the mobile WiFi devices) has been evaluated and compared with that of the standard operator-controlled WiFi hotspots

Adaptive relay techniques for OFDM-based cooperative communication systems

Cooperative communication has been considered as a cost-effective manner to exploit the spatial diversity, improve the quality-of-service and extend transmission coverage. However, there are many challenges faced by cooperative systems which use relays to forward signals to the destination, such as the accumulation of multipath channels, complex resource allocation with the bidirectional asymmetric traffic and reduction of transmission efficiency caused by additional relay overhead. In this thesis, we aim to address the above challenges of cooperative communications, and design the efficient relay systems. Starting with the channel accumulation problem in the amplify-and-forward relay system, we proposed two adaptive schemes for single/multiple-relay networks respectively. These schemes exploit an adaptive guard interval (GI) technique to cover the accumulated delay spread and enhance the transmission efficiency by limiting the overhead. The proposed GI scheme can be implemented without any extra control signal. Extending the adaptive GI scheme to multiple-relay systems, we propose a relay selection strategy which achieves the trade-off between the transmission reliability and overhead by considering both the channel gain and the accumulated delay spread. We then consider resource allocation problem in the two-way decode-and-forward relay system with asymmetric traffic loads. Two allocation algorithms are respectively investigated for time-division and frequency-division relay systems to maximize the end-to-end capacity of the two-way system under a capacity ratio constraint. For the frequency-division systems, a balanced end-to-end capacity is defined as the objective function which combines the requirements of maximizing the end-to-end capacity and achieving the capacity ratio. A suboptimal algorithm is proposed for the frequency-division systems which separates subcarrier allocation and time/power allocation. It can achieve the similar performance with the optimal one with reduced complexity. In order to further enhance the transmission reliability and maintaining low processing delay, we propose an equalize-and-forward (EF) relay scheme. The EF relay equalizes the channel between source and relay to eliminate the channel accumulation without signal regeneration. To reduce the processing time, an efficient parallel structure is applied in the EF relay. Numerical results show that the EF relay exhibits low outage probability at the same data rate as compared to AF and DF schemes

Direct Antenna Modulation using Frequency Selective Surfaces

In the coming years, the number of connected wireless devices will increase dramatically, expanding the Internet of Things (IoT). It is likely that much of this capacity will come from network densification. However, base stations are inefficient and expensive, particularly the downlink transmitters. The main cause of this is the power amplifier (PA), which must amplify complex signals, so are expensive and often only 30% efficient. As such, the cost of densifying cellular networks is high. This thesis aims to overcome this problem through codesign of a low complexity, energy efficient transmitter through electromagnetic design; and a waveform which leverages the advantages and mitigates the disadvantages of the new technology, while being suitable for supporting IoT devices. Direct Antenna Modulation (DAM) is a low complexity transmitter architecture, where modulation occurs at the antenna at transmit power. This means a non-linear PA can efficiently amplify the carrier wave without added distortion. Frequency Selective Surfaces (FSS) are presented here as potential phase modulators for DAM transmitters. The theory of operation is discussed, and a prototype DAM for QPSK modulation is simulated, designed and tested. Next, the design process for a continuous phase modulating antenna is explored. Simulations and measurement are used to fully characterise a prototype, and it is implemented in a line-of-sight end-to-end communications system, demonstrating BPSK, QPSK and 8-PSK. Due to the favourable effects of spread spectrum signalling on FSS DAM performance, Cyclic Prefix Direct Sequence Spread Spectrum (CPDSSS) is developed. Conventional spreading techniques are extended using a cyclic prefix, making multipath interference entirely defined by the periodic autocorrelation of the sequence used. This is demonstrated analytically, through simulation and with experiments. Finally, CPDSSS is implemented using FSS DAM, demonstrating the potential of this new low cost, low complexity transmitter with CPDSSS as a scalable solution to IoT connectivity