published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

In single-input multiple-output (SIMO) systems based on orthogonal frequency division multiplexing (OFDM), adaptive beamforming at the receiver side can be used to combat the effect of directional co-channel interference (CCI). Since pilot-aided beamforming suffers from consuming precious channel bandwidth, there has been much interest in blind beamforming approaches that can adapt their weights by restoring certain properties of the transmitted signals. Within this class of blind algorithms, the recursive least squares constant modulus algorithm (RLS-CMA) is of particular interest due to its good overall CCI cancelation performance and fast convergence. Nevertheless, the direct use of RSL-CMA within a SIMO-OFDM receiver induces considerable computational complexity, since a distinct copy of the RLS-CMA must be run on each individual sub-carriers. In this thesis, we present two approaches to reduce the computational complexity of SIMO-OFDM beamforming based on the RLS-CMA, namely: frequency interpolation and distributed processing. The former approach, which exploits the coherence bandwidth of the broadband wireless channels, divides the sub-carriers into several contiguous groups and applies the RLS-CMA to a selected sub-carrier in each group. The weight vectors at other frequencies are then obtained by interpolation. The distributed processing approach relies on the partitioning of the receiving array into sub-arrays and the use of a special approximation in the RLS-CMA. This allows a partial decoupling of the algorithm which can then be run on multiple processors with reduced overall complexity. This approach is well-suited to collaborative beamforming i~ multi-node distributed relaying. Through numerical simulation experiments of a SIMO-OFDM system, it is demonstrated that the proposed modifications to the RLS-CMA scheme can lead to substantial computational savings with minimal losses in adaptive cancelation performance.

Cognitive radio (CR) is a novel wireless communication approach that may alleviate the looming spectrum-shortage crisis. Orthogonal frequency division multiplexing (OFDM) is an attractive modulation candidate for CR systems. In this thesis, we study resource allocation (RA) for OFDM-based CR systems using both aggressive and protective sharing. In aggressive sharing, cognitive radio users (CRUs) can share both non-active and active primary user (PU) bands. We develop a model that describes aggressive sharing, and formulate a corresponding multidimensional knapsack problem (MDKP). Low-complexity suboptimal RA algorithms are proposed for both single and multiple CRU systems. A simplified model is proposed which provides a faster suboptimal solution. Simulation results show that the proposed suboptimal solutions are close to optimal, and that aggressive sharing of the whole band can provide a substantial performance improvement over protective sharing, which makes use of only the non-active PU bands. Although aggressive sharing generally yields a higher spectrum-utilization efficiency than protective sharing, aggressive sharing may not be feasible in some situations. In such cases, sharing only non-active PU bands is more appropriate. When there are no fairness or quality of service (QoS) considerations among CRUs, both theoretical analysis and simulation results show that plain equal power allocation (PEPA) yields similar performance as optimal power allocation in a multiuser OFDM-based CR system. We propose a low-complexity discrete bit PEPA algorithm. To improve spectrum-utilization efficiency, while considering the time-varying nature of the available spectrum as well as the fading characteristics of wireless communication channels and providing QoS provisioning and fairness among users, this thesis introduces the following novel algorithms: (1) a distributed RA algorithm that provides both fairness and efficient spectrum usage for ad hoc systems; (2) a RA algorithm for non-real-time (NRT) services that maintains average user rates proportionally on the downlink of multiuser OFDM-based CR systems; and (3) cross-layer RA algorithms for the downlink of multiuser OFDM-based CR systems for both real-time (RT) services and mixed (RT and NRT) services. Simulation results show that the proposed algorithms provide satisfactory QoS to all supported services and perform better than existing algorithms designed for multiuser OFDM systems.

We present a vision for 4G cellular networks based on the concept of autonomous infrastructure deployment. Cellular base stations, or femtocell access points, are deployed by network users without being constrained by the conventional cell planning process from the network operator. Autonomous deployment allows the network to grow in an organic manner which requires new methods for spectrum management. We study a framework for autonomous network optimization based on the method of cognitive interference management. In our model, a number of femtocells are co-channel deployed in an underlay macrocellular network. Instead of fully reusing 100% of the macrocellular resource, partial reuse is cognitively determined in femtocells based on their individual network environment. According to an interference signature perceived from the environment, a femtocell autonomously determines the appropriate channel allocation and minimizes the network interference. Upon the cognitive acquisition of the random infrastructure topology, base station pilot power is autonomously configured in order to maximize the cellular coverage. A series of network self-configuration procedures are discussed for automatic cell size adaptation and resource management. Our results show that the new approaches based on cognitive radio configuration facilitate the network optimization in terms of interference management, mobile handoff, pilot power control and network resource allocation. The proposed framework offers a 4G vision for spectrum management in an autonomous self-managed cellular architecture.

We present a vision for 4G cellular networks based on the concept of autonomous infrastructure deployment. Cellular base stations, or femtocell access points, are deployed by network users without being constrained by the conventional cell planning process from the network operator. Autonomous deployment allows the network to grow in an organic manner which requires new methods for spectrum management. We study a framework for autonomous network optimization based on the method of cognitive interference management. In our model, a number of femtocells are co-channel deployed in an underlay macrocellular network. Instead of fully reusing 100% of the macrocellular resource, partial reuse is cognitively determined in femtocells based on their individual network environment. According to an interference signature perceived from the environment, a femtocell autonomously determines the appropriate channel allocation and minimizes the network interference. Upon the cognitive acquisition of the random infrastructure topology, base station pilot power is autonomously configured in order to maximize the cellular coverage. A series of network self-configuration procedures are discussed for automatic cell size adaptation and resource management. Our results show that the new approaches based on cognitive radio configuration facilitate the network optimization in terms of interference management, mobile handoff, pilot power control and network resource allocation. The proposed framework offers a 4G vision for spectrum management in an autonomous self-managed cellular architecture.

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The rapidly growing need for fast and reliable transmission over a wireless channel motivates the development of communication systems that can support high data rates at low complexity. Achieving reliable communication over a wireless channel is a challenging task largely due to the possibility of multipaths which may lead to intersymbol interference (ISI). Diversity techniques such as time, frequency and space are commonly used to combat multipath fading. Classical diversity techniques use repetition codes such that the information is replicated and transmitted over several channels that are sufficiently spaced. In fading channels, the performance across some diversity branches may be excessively attenuated, making throughput unacceptably small. In principle, more powerful coding techniques can be used to maximize the diversity order. This leads to bandwidth expansion or increased transmission power to accommodate the redundant bits. Hence there is need for coding and modulation schemes that provide low error rate performance in a bandwidth efficient manner. If diversity schemes are combined, more independent dimensions become available for information transfer. The first part of the thesis addresses achieving temporal diversity through employing error correcting coding schemes combined with interleaving. Noncoherent differential modulation does not require explicit knowledge or estimate of the channel, instead the information is encoded in the transitions. This lends itself to the possibility of turbo-like serial concatenation of a standard outer channel encoder with an inner modulation code amenable to noncoherent detection through an interleaver. An iterative approach to joint decoding and demodulation can be realized by exchanging soft information between the decoder and the demodulator. This has been shown to be effective and hold hope for approaching capacity over fast fading channels. However most of these schemes employ low rate convolutional codes as their channel encoders. In this thesis we propose the use of redundant residue number system codes. It is shown that these codes can achieve comparable performance at minimal complexity and high data rates. The second part deals with the possibility of combining several diversity dimensions into a reliable bandwidth efficient communication scheme. Orthogonal frequency division multiplexing (OFDM) has been used to combat multipaths. Combining OFDM with multiple-input multiple-output (MIMO) systems to form MIMO-OFDM not only reduces the complexity by eliminating the need for equalization but also provides large channel capacity and a high diversity potential. Space-time coded OFDM was proposed and shown to be an effective transmission technique for MIMO systems. Spacefrequency coding and space-time-frequency coding were developed out of the need to exploit the frequency diversity due to multipaths. Most of the proposed schemes in the literature maximize frequency diversity predominantly from the frequency-selective nature of the fading channel. In this thesis we propose the use of residue number system as the frequency encoder. It is shown that the proposed space-time-frequency coding scheme can maximize the diversity gains over space, time and frequency domains. The gain of MIMO-OFDM comes at the expense of increased receiver complexity. Furthermore, most of the proposed space-time-frequency coding schemes assume frequency selective block fading channels which is not an ideal assumption for broadband wireless communications. Relatively high mobility in broadband wireless communications systems may result in high Doppler frequency, hence time-selective (rapid) fading. Rapidly changing channel characteristics impedes the channel estimation process and may result in incorrect estimates of the channel coefficients. The last part of the thesis deals with the performance of differential space-time-frequency coding in fast fading channels. / Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2007.