Enabling Technologies for Next Generation Wireless Local Area Networks (WLANs)

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Enabling Technologies for Next Generation Wireless Local Area Networks (WLANs)

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Title: Enabling Technologies for Next Generation Wireless Local Area Networks (WLANs)
Author(s):
Mohamed, Ahmed Gamal Helmy;
0000-0002-8039-7049
Advisor: Al-Dhahir, Naofal
Date Created: 2017-05
Format: Dissertation
Keywords: Show Keywords
Abstract: Next-generation wireless local area networks (WLANs) address two major challenges. The first is the flexibility to provide significantly increased users’ throughput due to the current evolution of the Internet usage toward real-time high-definition video content. Multi-input multi-output (MIMO) transmission at both access points (APs) and stations (STAs) is one of the key technologies to achieve high throughput in WLANs for both single-user MIMO (SUMIMO) and downlink multi-user MIMO (MU-MIMO). This requires APs and STAs to efficiently communicate while addressing challenging design trade-offs between energy efficiency, implementation complexity, and overall network spectral efficiency. In current WLANs, implementing MIMO techniques for SU-MIMO, which utilizes multiple radio-frequency (RF) chains, has become the norm. Thus, using a small number of RF chains, and ideally a single RF chain, is highly desirable for future low-power devices. The second challenge is dense deployment scenarios where many heterogeneous devices, from high-end laptops to low-power Internet of Things (IoT) devices and wearables, must coexist and operate reliably. In these dense scenarios, most relevant challenges in MU-MIMO are related to interference issues, which increase the packet error. In this dissertation, we focus on enhancing the user experience in SU-MIMO transmission and improving interference management techniques in MU-MIMO transmission for dense deployment WLAN scenarios. For SU-MIMO, we adopt Spatial Modulation (SM) as a single- (or few-) RF MIMO transmission technique that efficiently uses multiple antennas while addressing challenging design trade-offs between energy efficiency, implementation complexity, and overall network spectral efficiency. This motivates SM-based transmission for low-power IoT devices providing a better user experience for dense environments. We analyze the robustness of SM-based direct-conversion transceivers under transmit in-phase/quadrature (I/Q) imbalance. Then, we propose temporal modulation as a new dimension to enhance the performance of spatially modulated space-time block codes (STBC) while achieving a full transmit diversity order. Based on our proposed codebook, we propose the first differential transmission scheme for spatial modulation with multiple active transmit antennas. For the multi-stream MU-MIMO interference networks, we study the problem of per-stream maximum sum-rate (MSR) joint precoder and minimum mean-squared error (MMSE) equalizer design for the scenarios where multiple independent transmitters send data streams to corresponding different receivers via a shared channel forming an interference environment. We propose a generalized iterative algorithm which directly maximizes the sum-rate without assuming the signal-to-noise ratio (SNR) to be infinite. To reduce complexity, which can become prohibitive for large network size, we examine the performance-complexity tradeoffs involved in a sparse equalizer design. Joint precoder and equalizer optimization requires alternation between the forward and reverse links and assumes perfect synchronization between the transmitters and receivers at each network node, resulting in extensive overhead and spectral efficiency loss. To overcome this serious drawback, we propose a new design approach based on weighted-sum-rate maximization assuming a virtual equalizer type at the transmitter to limit the optimization process to the transmitter side. Finally, we quantify the sum-rate loss due to mismatched equalizer types and demonstrate the robustness of our proposed sum-rate weighting strategy to such mismatches with perfect or imperfect channel knowledge.
Degree Name: PHD
Degree Level: Doctoral
Persistent Link: http://hdl.handle.net/10735.1/5396
Type : text
Degree Program: Electrical Engineering

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