Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users

In downlink multi-antenna systems with many users, the multiplexing gain is strictly limited by the number of transmit antennas $N$ and the use of these antennas. Assuming that the total number of receive antennas at the multi-antenna users is much larger than $N$, the maximal multiplexing gain can be achieved with many different transmission/reception strategies. For example, the excess number of receive antennas can be utilized to schedule users with effective channels that are near-orthogonal, for multi-stream multiplexing to users with well-conditioned channels, and/or to enable interference-aware receive combining. In this paper, we try to answer the question if the $N$ data streams should be divided among few users (many streams per user) or many users (few streams per user, enabling receive combining). Analytic results are derived to show how user selection, spatial correlation, heterogeneous user conditions, and imperfect channel acquisition (quantization or estimation errors) affect the performance when sending the maximal number of streams or one stream per scheduled user---the two extremes in data stream allocation. While contradicting observations on this topic have been reported in prior works, we show that selecting many users and allocating one stream per user (i.e., exploiting receive combining) is the best candidate under realistic conditions. This is explained by the provably stronger resilience towards spatial correlation and the larger benefit from multi-user diversity. This fundamental result has positive implications for the design of downlink systems as it reduces the hardware requirements at the user devices and simplifies the throughput optimization.Comment: Published in IEEE Transactions on Signal Processing, 16 pages, 11 figures. The results can be reproduced using the following Matlab code: https://github.com/emilbjornson/one-or-multiple-stream

Cooperative diversity for the cellular uplink: Sharing strategies, performance analysis, and receiver design

In this thesis, we propose data sharing schemes for the cooperative diversity in a cellular uplink to exploit diversity and enhance throughput performance of the system. Particularly, we consider new two and three-or-more user decode and forward (DF) protocols using space time block codes. We discuss two-user and three-user amplify and forward (AF) protocols and evaluate the performance of the above mentioned data sharing protocols in terms of the bit error rate and the throughput in an asynchronous code division multiple access (CDMA) cellular uplink. We develop a linear receiver for joint space-time decoding and multiuser detection that provides full diversity and near maximum-likelihood performance.;We also focus on a practical situation where inter-user channel is noisy and cooperating users can not successfully estimate other user\u27s data. We further design our system model such that, users decide not to forward anything in case of symbol errors. Channel estimation plays an important role here, since cooperating users make random estimation errors and the base station can not have the knowledge of the errors or the inter-user channels. We consider a training-based approach for channel estimation. We provide an information outage probability analysis for the proposed multi-user sharing schemes. (Abstract shortened by UMI.)

Fractionally sampled decorrelating detectors for time-varying rayleigh fading CDMA channels

In this dissertation, we propose novel decorrelating multiuser detectors in DSCDMA time-varying frequency-nonselective and frequency-selective fading channels and analyze their performance. We address the common shortcomings of existing multiuser detectors in a mobile environment, such as detector complexity and the error floor. An analytical approach is employed almost exclusively and Monte Carlo simulation is used to confirm the theoretical results. Practical channel models, such as Jakes\u27 and Markovian, are adopted in the numerical examples. The proposed detectors are of the decorrelating type and utilize fractional sampling to simultaneously achieve two goals: (1) the novel realization of a decorrelator with lower computational complexity and shorter processing latency; and (2) the significant reduction of the probability of error floor associated with time-varying fading. The analysis of the impact of imperfect power control on IS-95 multiple access interference is carried out first and the ineffectiveness of IS-95 power control in a mobile radio environment is demonstrated. Fractionally-spaced bit-by-bit decorrelator structures for the frequency-nonselective and frequency-selective channels are then proposed. The matrix singularity problem associated with decorrelation is also addressed, and its solution is suggested. A decorrelating receiver employing differentially coherent detection for an asynchronous CDMA, frequency-nonselective time-varying Rayleigh fading channel is proposed. A maximum likelihood detection principle is applied at the fractionally spaced decorrelator output, resulting in a significantly reduced error floor. For coherent detection, a novel single-stage and two-stage decision feedback (DF) maximum a posteriori (MAP) channel estimator is proposed. These estimators are applicable to a channel with an arbitrary spaced-time correlation function. The fractionally-spaced decorrelating detector is then modified and extended to a frequency-selective time-varying fading channel, and is shown to be capable of simultaneously eliminating MAI, ISI, and path cross-correlation interference. The implicit equivalent frequency diversity is exploited through multipath combining, and the effective time diversity is achieved by fractional sampling for significant performance improvement. The significance of the outcome of this research is in the design of new lower complexity multiuser detectors that do not exhibit the usual deficiencies and limitations associated with a time-varying fading and multipath CDMA mobile environment

Intelligent Approaches for Energy-Efficient Resource Allocation in the Cognitive Radio Network

The cognitive radio (CR) is evolved as the promising technology to alleviate the spectrum scarcity issues by allowing the secondary users (SUs) to use the licensed band in an opportunistic manner. Various challenges need to be addressed before the successful deployment of CR technology. This thesis work presents intelligent resource allocation techniques for improving energy efficiency (EE) of low battery powered CR nodes where resources refer to certain important parameters that directly or indirectly affect EE. As far as the primary user (PU) is concerned, the SUs are allowed to transmit on the licensed band until their transmission power would not cause any interference to the primary network. Also, the SUs must use the licensed band efficiently during the PU’s absence. Therefore, the two key factors such as protection to the primary network and throughput above the threshold are important from the PU’s and SUs’ perspective, respectively. In deployment of CR, malicious users may be more active to prevent the CR users from accessing the spectrum or cause unnecessary interference to the both primary and secondary transmission. Considering these aspects, this thesis focuses on developing novel approaches for energy-efficient resource allocation under the constraints of interference to the PR, minimum achievable data rate and maximum transmission power by optimizing the resource parameters such as sensing time and the secondary transmission power with suitably selecting SUs. Two different domains considered in this thesis are the soft decision fusion (SDF)-based cooperative spectrum sensing CR network (CRN) models without and with the primary user emulation attack (PUEA). An efficient iterative algorithm called iterative Dinkelbach method (IDM) is proposed to maximize EE with suitable SUs in the absence of the attacker. In the proposed approaches, different constraints are evaluated considering the negative impact of the PUE attacker on the secondary transmission while maximizing EE with the PUE attacker. The optimization problem associated with the non-convex constraints is solved by our proposed iterative resource allocation algorithms (novel iterative resource allocation (NIRA) and novel adaptive resource allocation (NARA)) with suitable selection of SUs for jointly optimizing the sensing time and power allocation. In the CR enhanced vehicular ad hoc network (CR-VANET), the time varying channel responses with the vehicular movement are considered without and with the attacker. In the absence of the PUE attacker, an interference-aware power allocation scheme based on normalized least mean square (NLMS) algorithm is proposed to maximize EE considering the dynamic constraints. In the presence of the attacker, the optimization problem associated with the non-convex and time-varying constraints is solved by an efficient approach based on genetic algorithm (GA). Further, an investigation is attempted to apply the CR technology in industrial, scientific and medical (ISM) band through spectrum occupancy prediction, sub-band selection and optimal power allocation to the CR users using the real time indoor measurement data. Efficacies of the proposed approaches are verified through extensive simulation studies in the MATLAB environment and by comparing with the existing literature. Further, the impacts of different network parameters on the system performance are analyzed in detail. The proposed approaches will be highly helpful in designing energy-efficient CRN model with low complexity for future CR deployment

Modern Random Access for Satellite Communications

The present PhD dissertation focuses on modern random access (RA) techniques. In the first part an slot- and frame-asynchronous RA scheme adopting replicas, successive interference cancellation and combining techniques is presented and its performance analysed. The comparison of both slot-synchronous and asynchronous RA at higher layer, follows. Next, the optimization procedure, for slot-synchronous RA with irregular repetitions, is extended to the Rayleigh block fading channel. Finally, random access with multiple receivers is considered.Comment: PhD Thesis, 196 page

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

Shannon Meets Nyquist: Capacity of Sampled Gaussian Channels

We explore two fundamental questions at the intersection of sampling theory and information theory: how channel capacity is affected by sampling below the channel's Nyquist rate, and what sub-Nyquist sampling strategy should be employed to maximize capacity. In particular, we derive the capacity of sampled analog channels for three prevalent sampling strategies: sampling with filtering, sampling with filter banks, and sampling with modulation and filter banks. These sampling mechanisms subsume most nonuniform sampling techniques applied in practice. Our analyses illuminate interesting connections between under-sampled channels and multiple-input multiple-output channels. The optimal sampling structures are shown to extract out the frequencies with the highest SNR from each aliased frequency set, while suppressing aliasing and out-of-band noise. We also highlight connections between undersampled channel capacity and minimum mean-squared error (MSE) estimation from sampled data. In particular, we show that the filters maximizing capacity and the ones minimizing MSE are equivalent under both filtering and filter-bank sampling strategies. These results demonstrate the effect upon channel capacity of sub-Nyquist sampling techniques, and characterize the tradeoff between information rate and sampling rate.Comment: accepted to IEEE Transactions on Information Theory, 201

Multi-carrier CDMA using convolutional coding and interference cancellation

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