EXIT-charts-aided hybrid multiuser detector for multicarrier interleave-division multiple access

A generically applicable hybrid multiuser detector (MUD) concept is proposed by appropriately activating different MUDs in consecutive turbo iterations based on the mutual information (MI) gain. It is demonstrated that the proposed hybrid MUD is capable of approaching the optimal Bayesian MUD's performance despite its reduced complexity, which is at a modestly increased complexity in comparison with that of the suboptimum soft interference cancellation (SoIC) MU

Semi-blind channel estimation for multiuser OFDM-IDMA systems.

M. Sc. Eng. University of KwaZulu-Natal, Durban 2014.Over the last decade, the data rate and spectral efficiency of wireless mobile communications have been significantly enhanced. OFDM technology has been used in the development of advanced systems such as 3GPP LTE and terrestrial digital TV broadcasting. In general, bits of information in mobile communication systems are conveyed through radio links to receivers. The radio channels in mobile radio systems are usually multipath fading channels, which cause inter-symbol interference (ISI) in the received signal. The ability to know the channel impulse response (CIR) and Channel State Information (CSI) helps to remove the ISI from the signal and make coherent detection of the transmitted signal at the receiver end of the system easy and simple. The information about CIR and CSI are primarily provided by channel estimation. This thesis is focused on the development of multiple access communication technique, Multicarrier Interleave Division Multiple Access (MC-IDMA) and the corresponding estimation of the system channel. It compares various efficient channel estimation algorithms. Channel estimation of OFDM-IDMA scheme is important because the emphasis from previous studies assumed the implementation of MC-IDMA in a perfect scenario, where Channel State Information (CSI) is known. MC-IDMA technique incorporates three key features that will be common to the next generation communication systems; multiple access capability, resistance to multipath fading and high bandwidth efficiency. OFDM is almost completely immune to multipath fading effects and IDMA has a recently proposed multiuser capability scheme which employs random interleavers as the only method for user separation. MC-IDMA combines the features of OFDM and IDMA to produce a system that is Inter Symbol Interference (ISI) free and has higher data rate capabilities for multiple users simultaneously. The interleaver property of IDMA is used by MC-IDMA as the only means by which users are separated at the receiver and also its entire bandwidth expansion is devoted to low rate Forward Error Correction (FEC). This provides additional coding gain which is not present in conventional Multicarrier Multiuser systems, (MC-MU) such as Code Division Multiple Access (CDMA), Multicarrier-Code Division Multiple Access (MC-CDMA) systems, and others. The effect of channel fading and both cross-cell and intra-cell Multiple Access Interference (MAI) in MC-IDMA is suppressed efficiently by its low-cost turbo-type Chip-by-Chip (CBC) multiuser detection algorithm. We present the basic principles of OFDM-IDMA transmitter and receiver. Comparative studies between Multiple Access Scheme such as Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), CDMA and IDMA are carried out. A linear Minimum Mean Square Error (MMSE)-based estimation algorithm is adopted and implemented. This proposed algorithm is a non-data aided method that focuses on obtaining the CSI, remove ISI and reduce the complexity of the MMSE algorithm. However, to obtain a better and improved system performance, an improved MMSE algorithm and simplified MMSE using the structured correlation and reduced auto-covariance matrix are developed in this thesis and proposed for implementation of semi-blind channel estimation in OFDM-IDMA communication systems. The effectiveness of the adopted and proposed algorithms are implemented in a Rayleigh fading multipath channel with varying mobile speeds thus demonstrating the performance of the system in a practical scenario. Also, the implemented algorithms are compared to ascertain which of these algorithms offers a better and more efficient system performance, and with less complexity. The performance of the channel estimation algorithm is presented in terms of the mean square error (MSE) and bit error rate (BER) in both slow fading and fast fading multipath scenarios and the results are documented as well

Joint Communication and Positioning based on Channel Estimation

Mobile wireless communication systems have rapidly and globally become an integral part of everyday life and have brought forth the internet of things. With the evolution of mobile wireless communication systems, joint communication and positioning becomes increasingly important and enables a growing range of new applications. Humanity has already grown used to having access to multimedia data everywhere at every time and thereby employing all sorts of location-based services. Global navigation satellite systems can provide highly accurate positioning results whenever a line-of-sight path is available. Unfortunately, harsh physical environments are known to degrade the performance of existing systems. Therefore, ground-based systems can assist the existing position estimation gained by satellite systems. Determining positioning-relevant information from a unified signal structure designed for a ground-based joint communication and positioning system can either complement existing systems or substitute them. Such a system framework promises to enhance the existing systems by enabling a highly accurate and reliable positioning performance and increased coverage. Furthermore, the unified signal structure yields synergetic effects. In this thesis, I propose a channel estimation-based joint communication and positioning system that employs a virtual training matrix. This matrix consists of a relatively small training percentage, plus the detected communication data itself. Via a core semi- blind estimation approach, this iteratively includes the already detected data to accurately determine the positioning-relevant parameter, by mutually exchanging information between the communication part and the positioning part of the receiver. Synergy is created. I propose a generalized system framework, suitable to be used in conjunction with various communication system techniques. The most critical positioning-relevant parameter, the time-of-arrival, is part of a physical multipath parameter vector. Estimating the time-of-arrival, therefore, means solving a global, non-linear, multi-dimensional optimization problem. More precisely, it means solving the so-called inverse problem. I thoroughly assess various problem formulations and variations thereof, including several different measurements and estimation algorithms. A significant challenge, when it comes to solving the inverse problem to determine the positioning-relevant path parameters, is imposed by realistic multipath channels. Most parameter estimation algorithms have proven to perform well in moderate multipath environments. It is mathematically straightforward to optimize this performance in the sense that the number of observations has to exceed the number of parameters to be estimated. The typical parameter estimation problem, on the other hand, is based on channel estimates, and it assumes that so-called snapshot measurements are available. In the case of realistic channel models, however, the number of observations does not necessarily exceed the number of unknowns. In this thesis, I overcome this problem, proposing a method to reduce the problem dimensionality via joint model order selection and parameter estimation. Employing the approximated and estimated parameter covariance matrix inherently constrains the estimation problem’s model order selection to result in optimal parameter estimation performance and hence optimal positioning performance. To compare these results with the optimally achievable solution, I introduce a focused order-related lower bound in this thesis. Additionally, I use soft information as a weighting matrix to enhance the positioning algorithm positioning performance. For demonstrating the feasibility and the interplay of the proposed system components, I utilize a prototype system, based on multi-layer interleave division multiple access. This proposed system framework and the investigated techniques can be employed for multiple existing systems or build the basis for future joint communication and positioning systems. The assessed estimation algorithms are transferrable to all kinds of joint communication and positioning system designs. This thesis demonstrates their capability to, in principle, successfully cope with challenging estimation problems stemming from harsh physical environments

Multiple Access Techniques for Next Generation Wireless: Recent Advances and Future Perspectives

The advances in multiple access techniques has been one of the key drivers in moving from one cellular generation to another. Starting from the first generation, several multiple access techniques have been explored in different generations and various emerging multiplexing/multiple access techniques are being investigated for the next generation of cellular networks. In this context, this paper first provides a detailed review on the existing Space Division Multiple Access (SDMA) related works. Subsequently, it highlights the main features and the drawbacks of various existing and emerging multiplexing/multiple access techniques. Finally, we propose a novel concept of clustered orthogonal signature division multiple access for the next generation of cellular networks. The proposed concept envisions to employ joint antenna coding in order to enhance the orthogonality of SDMA beams with the objective of enhancing the spectral efficiency of future cellular networks

Iterative Detection for Overloaded Multiuser MIMO OFDM Systems

Inspired by multiuser detection (MUD) and the ‘Turbo principle’, this thesis deals with iterative interference cancellation (IIC) in overloaded multiuser multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Linear detection schemes, such as zero forcing (ZF) and minimum mean square error (MMSE) cannot be used for the overloaded system because of the rank deficiency of channel matrix, while the optimal approach, the maximum likelihood (ML) detection has high computational complexity. In this thesis, an iterative interference cancellation (IIC) multiuser detection scheme with matched filter and convolutional codes is considered. The main idea of this combination is a low complexity receiver. Parallel interference cancellation (PIC) is employed to improve the multiuser receiver performance for overloaded systems. A log-likelihood ratio (LLR) converter is proposed to further improve the reliability of the soft value converted from the output of the matched filter. Simulation results show that the bit error rate (BER) performance of this method is close to the optimal approach for a two user system. However, for the four user or more user system, it has an error floor of the BER performance. For this case, a channel selection scheme is proposed to distinguish whether the channel is good or bad by using the mutual information based on the extrinsic information transfer (EXIT) chart. The mutual information can be predicted in a look-up table which greatly reduces the complexity. For those ‘bad’ channels identified by the channel selection, we introduce two adaptive transmission methods to deal with such channels: one uses a lower code rate, and the other is multiple transmissions. The use of an IIC receiver with the interleave-division multiple access (IDMA) to further improve the BER performance without any channel selection is also investigated. It has been shown that this approach can remove the error floor. Finally, the influence of channel accuracy on the IIC is investigated. Pilot-based Wiener filter channel estimation is used to test and verify how much the IIC is influenced by the channel accuracy

Joint transmit power allocation and splitting for swipt aided OFDM-IDMA in wireless sensor networks

In this paper, we propose to combine Orthogonal Frequency Division Multiplexing-Interleave Division Multiple Access (OFDM-IDMA) with Simultaneous Wireless Information and Power Transfer (SWIPT), resulting in SWIPT aided OFDM-IDMA scheme for power-limited sensor networks. In the proposed system, the Receive Node (RN) applies Power Splitting (PS) to coordinate the Energy Harvesting (EH) and Information Decoding (ID) process, where the harvested energy is utilized to guarantee the iterative Multi-User Detection (MUD) of IDMA to work under sufficient number of iterations. Our objective is to minimize the total transmit power of Source Node (SN), while satisfying the requirements of both minimum harvested energy and Bit Error Rate (BER) performance from individual receive nodes. We formulate such a problem as a joint power allocation and splitting one, where the iteration number of MUD is also taken into consideration as the key parameter to affect both EH and ID constraints. To solve it, a sub-optimal algorithm is proposed to determine the power profile, PS ratio and iteration number of MUD in an iterative manner. Simulation results verify that the proposed algorithm can provide significant performance improvement