Wireless networks are undergoing an unprecedented revolution in the last decade. With the explosion of delay-sensitive applications in the Internet (i.e., online gaming and VoIP), latency becomes a major issue for the development of wireless technology. Taking advantage of the significant decline in memory prices, industrialists equip the network devices with larger buffering capacities to improve the network throughput by limiting packets drops. Over-buffering results in increasing the time that packets spend in the queues and, thus, introducing more latency in networks. This phenomenon is known as “bufferbloat”. While throughput is the dominant performance metric, latency also has a huge impact on user experience not only for real-time applications but also for common applications like web browsing, which is sensitive to latencies in order of hundreds of milliseconds. Concerns have arisen about designing sophisticated queue management schemes to mitigate the effects of such phenomenon. My thesis research aims to solve bufferbloat problem in both traditional half-duplex and cutting-edge full-duplex wireless systems by reducing delay while maximizing wireless links utilization and fairness. Our work shed lights on buffer management algorithms behavior in wireless networks and their ability to reduce latency resulting from excessive queuing delays inside oversized static network buffers without a significant loss in other network metrics. First of all, we address the problem of buffer management in wireless full-duplex networks by using Wireless Queue Management (WQM), which is an active queue management technique for wireless networks. Our solution is based on Relay Full-Duplex MAC (RFD-MAC), an asynchronous media access control protocol designed for relay full-duplexing. Compared to the default case, our solution reduces the end-to-end delay by two orders of magnitude while achieving similar throughput in most of the cases. In the second part of this thesis, we propose a novel design called “LearnQueue” based on reinforcement learning that can effectively control the latency in wireless networks. LearnQueue adapts quickly and intelligently to changes in the wireless environment using a sophisticated reward structure. Testbed results prove that LearnQueue can guarantee low latency while preserving throughput.

Wireless services have become an indispensable part of our social, economic, and everyday activities. They have facilitated and continue to facilitate rapid access to information and have created a highly-interconnected web of users who are untethered to particular locations. In fact, it is expected that in the very near future, the number of users that access the Internet through their mobile devices will surpass those access the Internet from the fixed infrastructure. Aside from mobile Internet access, wireless technologies enable many critical applications such as emergency response, healthcare and implantable medical devices, industrial automation, tactical communications, transportation networks, smart grids, smart homes, navigation, and weather services. The proliferation and wealth of wireless applications has created a soaring demand for ubiquitous broadband wireless access. This demand is further fueled by the richness of the information accessed by users. Low-bit rate voice communications and text have been replaced with graphics, high-definition video, multi-player gaming, and social networking. Meeting the growing traffic demand poses many challenges due to the spectrum scarcity, the cost of deploying additional infrastructure, and the coexistence of several competing technologies. These challenges can be addressed by developing novel wireless technologies, which can efficiently and securely manage multi-user access to the wireless medium. The multi-user access problem deals with the sharing of the wireless resource among contending users in an efficient, secure, and scalable manner. To alleviate contention and interference among the multiple users, contemporary wireless technologies divide the available spectrum to orthogonal frequency bands (channels). The availability of multiple channels has been demonstrated to substantially improve the performance and reliability of wireless networks by alleviating contention and interference. Multi-channel networks, whether cellular, sensor, mesh, cognitive radio, or heterogeneous ones, can potentially achieve higher throughput and lower delay compared to single-channel networks. However, the gains from the existence of orthogonal channels are contingent upon the efficient and secure coordination of channel access. Typically, this coordination is implemented at the medium access control (MAC) layer using a multi-channel MAC (MMAC) protocol. MMAC protocols are significantly more sophisticated than their single-channel counterparts, due to the additional operations of destination discovery, contention management across channels, and load balancing. A significant body of research has been devoted to designing MMAC protocols. The majority of solutions negotiate channel assignment every few packet transmissions on a default control channel. This design has several critical limitations. First, it incurs significant overhead due to the use of in-band or out-of-band control channels. Second, from a security standpoint, operating over a default control channel constitutes a single point of failure. A DoS attack on the control channel(s) would render all channels inoperable. Moreover, MMAC protocols are vulnerable to misbehavior from malicious users who aim at monopolizing the network resources, or degrading the overall network performance. In this dissertation, we improve the security and spectral efficiency of channel access mechanisms in multi-channel wireless networks. In particular, we are concerned with MAC-layer misbehavior in multi-channel wireless networks. We show that selfish users can manipulate MAC-layer protocol parameters to gain an unfair share of network resources, while remaining undetected. We identify possible misbehavior at the MAC-layer, evaluate their impact on network performance, and develop corresponding detection and mitigation schemes that practically eliminate the misbehavior gains. We extend our misbehavior analysis to MAC protocols specifically designed for opportunistic access in cognitive radio networks. Such protocols implement additional tasks such as cooperative spectrum sensing and spectrum management. We then discuss corresponding countermeasures for detecting and mitigating these misbehavior. We further design a low-overhead multi-channel access protocol that enables the distributed coordination of channel access over orthogonal channels for devices using a single transceiver. Compared with prior art, our protocol eliminates inband and out-of-band control signaling, increases spatial channel reuse, and thus achieves significant higher throughput and lowers delay. Furthermore, we investigate DoS attacks launched against the channel access mechanism. We focus on reactive jamming attacks and show that most MMAC protocols are vulnerable to low-effort jamming due to the utilization of a default control channel. We extend our proposed MMAC protocol to combat jamming by implementing cryptographic interleaving at the PHY-layer, random channel switching, and switching according to cryptographically protected channel priority lists. Our results demonstrate that under high load conditions, the new protocol maintains communications despite the jammer's effort. Extensive simulations and experiments are conducted to evaluate the impact of the considered misbehaviors on network performance, and verify the validity of the proposed mechanisms.

abstract: Both two-way relays (TWR) and full-duplex (FD) radios are spectrally efficient, and their integration shows great potential to further improve the spectral efficiency, which offers a solution to the fifth generation wireless systems. High quality channel state information (CSI) are the key components for the implementation and the performance of the FD TWR system, making channel estimation in FD TWRs crucial. The impact of channel estimation on spectral efficiency in half-duplex multiple-input-multiple-output (MIMO) TWR systems is investigated. The trade-off between training and data energy is proposed. In the case that two sources are symmetric in power and number of antennas, a closed-form for the optimal ratio of data energy to total energy is derived. It can be shown that the achievable rate is a monotonically increasing function of the data length. The asymmetric case is discussed as well. Efficient and accurate training schemes for FD TWRs are essential for profiting from the inherent spectrally efficient structures of both FD and TWRs. A novel one-block training scheme with a maximum likelihood (ML) estimator is proposed to estimate the channels between the nodes and the residual self-interference (RSI) channel simultaneously. Baseline training schemes are also considered to compare with the one-block scheme. The Cramer-Rao bounds (CRBs) of the training schemes are derived and analyzed by using the asymptotic properties of Toeplitz matrices. The benefit of estimating the RSI channel is shown analytically in terms of Fisher information. To obtain fundamental and analytic results of how the RSI affects the spectral efficiency, one-way FD relay systems are studied. Optimal training design and ML channel estimation are proposed to estimate the RSI channel. The CRBs are derived and analyzed in closed-form so that the optimal training sequence can be found via minimizing the CRB. Extensions of the training scheme to frequency-selective channels and multiple relays are also presented. Simultaneously sensing and transmission in an FD cognitive radio system with MIMO is considered. The trade-off between the transmission rate and the detection accuracy is characterized by the sum-rate of the primary and the secondary users. Different beamforming and combining schemes are proposed and compared. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

abstract: In-band full-duplex relays are envisioned as promising solution to increase the throughput of next generation wireless communications. Full-duplex relays, being able to transmit and receive at same carrier frequency, offers increased spectral efficiency compared to half-duplex relays that transmit and receive at different frequencies or times. The practical implementation of full-duplex relays is limited by the strong self-interference caused by the coupling of relay's own transit signals to its desired received signals. Several techniques have been proposed in literature to mitigate the relay self-interference. In this thesis, the performance of in-band full-duplex multiple-input multiple-output (MIMO) relays is considered in the context of simultaneous communications and channel estimation. In particular, adaptive spatial transmit techniques is considered to protect the full-duplex radio's receive array. It is assumed that relay's transmit and receive antenna phase centers are physically distinct. This allows the radio to employ adaptive spatial transmit and receive processing to mitigate self-interference. The performance of this protection is dependent upon numerous factors, including channel estimation accuracy, which is the focus of this thesis. In particular, the concentration is on estimating the self-interference channel. A novel approach of simultaneous signaling to estimate the self-interference channel in MIMO full-duplex relays is proposed. To achieve this simultaneous communications and channel estimation, a full-rank pilot signal at a reduced relative power is transmitted simultaneously with a low rank communication waveform. The self-interference mitigation is investigated in the context of eigenvalue spread of spatial relay receive co-variance matrix. Performance is demonstrated by using simulations, in which orthogonal-frequency division-multiplexing communications and pilot sequences are employed. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2014

To meet the urgent demand of high-speed data rate and to support large number of users, the massive multiple-input multiple-output (MIMO) technology is becoming one of the most promising candidates for the next generation wireless communications, namely the 5G. To realize the full potential of massive MIMO, it is necessary to have the channel state information (CSI) (partially) available at the transmitter. Hence, an efficient channel estimation is one of the key enablers and also critical challenges for 5G communications. Dealing with such problems, this dissertation investigates the design of efficient pilot-data transmission pattern and channel estimation in massive MIMO for both multipair relaying and peer-to-peer systems. Firstly, this dissertation proposes a pilot-data transmission overlay scheme for multipair MIMO relaying systems employing either half- or full-duplex (HD or FD) communications at the relay station (RS). In the proposed scheme, pilots are transmitted in partial overlap with data to decrease the channel estimation overhead. The RS can detect the source data by exploiting the asymptotic orthogonality of massive MIMO channels. Due to the transmission overlay, the effective data period is extended, hence improving system throughput. Both theoretical and simulation results verify that the proposed pilot-data overlay scheme outperforms the conventional separate pilot-data design in the limited coherence interval scenario. Moreover, a power allocation problem is formulated to properly adjust the transmission power of source data transmission and relay data forwarding which further improves the system performance. Additionally, this dissertation proposes and analyzes an efficient HD decode-and-forward (DF) scheme, named sum decode-and-forward (SDF), with the physical layer network coding (PNC) in the multipair massive MIMO two-way relaying system. As comparison, a joint decode-and-forward (JDF) scheme applied to the multipair massive MIMO relaying is also proposed and investigated. In the SDF scheme, a half number of pilots are saved compared to the JDF scheme which in turn increases the spectral efficiency of the system. Both the theoretical analyses and numerical results verifies such superiority of the SDF scheme. Further, the power efficiency of the proposed schemes is also investigated. Simulation results show that the signal transmission power can be rapidly reduced if the massive antenna arrays are equipped on the RS and the required data transmission power can further decrease if the training power is fixed. Finally, this dissertation investigates the general channel estimation problem in the massive MIMO system which employs the hybrid analog/digital precoding structure with limited radio-frequency (RF) chains. By properly designing RF combiners and performing multiple trainings, the performance of the proposed channel estimation can approach that of full-chain estimations depending on the degree of channel spatial correlation and the number of RF chains which is verified by simulation results in terms of both mean square error (MSE) and spectral efficiency. Moreover, a covariance matching method is proposed to obtain channel correlation in practice and the simulation verifies its effectiveness by evaluating the spectral efficiency performance in parametric channel models. / Graduate / 0537 / 0544 / leyuanpan@gmail.com

Improving spectral-utilization is a core focus to cater the ever-increasing demand in data rate and system capacity required for the development of 5G. This dissertation focuses on three spectrum-reuse technologies that are envisioned to play an important role in 5G networks: device-to-device (D2D), full-duplex (FD), and nonorthogonal multiple access (NOMA). D2D allows proximal user-equipments (UEs) to bypass the cellular base-station and communicate with their intended receiver directly. In underlay D2D, the D2D UEs utilize the same spectral resources as the cellular UEs. FD communication allows a transmit-receive pair to transmit simultaneously on the same frequency channel. Due to the overwhelming self-interference encountered, FD was not possible until very recently courtesy of advances in transceiver design. NOMA allows multiple receivers (transmitters) to communicate with one transmitter (receiver) in one time-frequency resource-block by multiplexing in the power domain. Successive-interference cancellation is used for NOMA decoding. Each of these techniques significantly improves spectral efficiency and consequently data rate and throughput; however, the price paid is increased interference. Since each of these technologies allow multiple transmissions within a cell on a time-frequency resource-block, they result in interference within the cell (i.e., intracell interference). Additionally, due to the increased communication, they increase network interference from outside the cell under consideration as well (i.e., increased intercell interference). Real networks are becoming very dense; as a result, the impact of intercell interference coming from the entire network is significant. As such, using models that consider a single-cell/few-cell scenarios result in misleading conclusions. Hence, accurate modeling requires considering a large network. In this context, stochastic geometry is a powerful tool for analyzing random patterns of points such as those found in wireless networks. In this dissertation, stochastic geometry is used to model and analyze the different technologies that are to be deployed in 5G networks. This gives us insight into the network performance, showing us the impacts of deploying a certain technology into real 5G networks. Additionally, it allows us to propose schemes for integrating such technologies, mode-selection, parameter-selection, and resource-allocation that enhance the parameters of interest in the network such as data rate, coverage, and secure communication.

The demand for wireless communication is ceaselessly increasing in terms of the number of subscribers and services. Future generations of cellular networks are expected to allow not only humans but also machines to be immersively connected. However, the radio frequency spectrum is already fully allocated. Therefore, developing techniques to increase spectrum efficiency has become necessary. This dissertation analyzes two spectrum sharing techniques that enable efficient utilization of the available radio resources in cellular networks. The first technique, called full-duplex (FD) communication, uses the same spectrum to transmit and receive simultaneously. Using stochastic geometry tools, we derive a closed-form expression of an upper-bound for the maximum achievable uplink ergodic rate in FD cellular networks. We show that the uplink transmission is vulnerable to the new interference introduced by FD communications (interference from the downlink transmission in other cells), especially when the disparity in transmission power between the uplink and downlink is considerable. We further show that adjusting the uplink transmission power according to the interference power level and the channel gain can improve the uplink performance in full-duplex cellular networks. Moreover, we propose an interference management technique that allows a flexible overlap between the spectra occupied by the downlink and uplink transmissions. The flexible overlap is optimized along with the user-to-base station association, the power allocation and the channel allocation in order to maximize a network-wide utility function. The second spectrum sharing technique, called non-orthogonal multiple access (NOMA), allows a transmitter to communicate with multiple receivers through the same frequency-time resource unit. We analyze the implementation of such a scheme in the downlink of cellular networks, more precisely, in the downlink of fog radio access networks (FogRANs). FogRAN is a network architecture that takes full advantage of the edge devices capability to process and store data. We propose managing the interference for NOMA-based FogRAN to improve the network performance by jointly optimizing user scheduling, the power allocated to each resource block and the division of power between the multiplexed users. The simulation results show that significant performance gains can be achieved through proper resource allocation with both studied spectrum sharing techniques.

In-band full-duplex, by which radios may simultaneously transmit and receive over the same channel, has been always considered practically-unfeasible due to the prohibitively strong self-interference. Indeed, a freshly-generated transmit signal power is typically ten orders of magnitude higher than that of a naturally-attenuated received signal. While unable to manage such an overwhelming interference, wireless communications resorted to half-duplex operation, transmitting and receiving over orthogonal channel resources. Recent research has demonstrated the practical feasibility of full-duplexing via successive sophisticated stages of signal suppression/cancellation, bringing this long-held assumption down and reviving the promising full-duplex potentials. Full-duplex relaying (FDR), where intermediate nodes may now support source-destination communication via simultaneous listening/forwarding, represents one of two full-duplex settings currently recommended for deployment in future fifth-generation (5G) systems. Theoretically, it has been widely accepted that FDR potentially doubles the channel capacity when compared to its half-duplex counterpart. Although FDR doubles the multiplexing gain, the effective signal-to-noise ratio (SNR) can be significantly degraded due to the residual self-interference (RSI) if not properly handled. In this work, efficient protocols are devised for different FDR settings. Selective cooperation is proposed for the canonical three-terminal FDR channel with RSI, which exploits the cooperative diversity offered by the independently fading source/relay message replicas arriving at the destination. Closed-form expressions are derived for the end-to-end SNR cumulative distribution function (CDF) under Rayleigh and Nakagami-m fading. Further, the offered diversity gain is presented as a function of the RSI scaling trend with the relay power. We show that the existing diversity problem in simple FDR protocols can be considerably fixed via block transmission with selective cooperation. Beyond the single-relay setting, the outage performance of different opportunistic full-duplex relay selection (FDRS) protocols is also evaluated under Rayleigh and Nakagami-m fading. It is shown that, with state-of-the-art adaptive self-interference cancellation techniques, FDRS can offer the same diversity order of its half-duplex rival while supporting a higher level of spectral efficiency. FDRS is also analyzed when adopted by a spectrum-sharing secondary system while the primary spectrum user imposes an additional interference constraint. Finally, buffer-aided hybrid half-/full-duplex cooperation is addressed. To maximize the end-to-end throughput, joint duplexing mode and link selection is studied where the system leverages the buffer and outage state information at the transmitters. All theoretic findings are corroborated with numerical simulations, with comparisons to existing protocols.

Next generation of wireless communication mostly relies on multiple-input multipleoutput (MIMO) configuration and full-duplex relaying to improve data-rates, spectrale efficiency, spatial-multiplexing, quality-of-service and energy-efficiency etc. However, multiple radio frequency (RF) transceivers in MIMO system and multi-hops in relay networks, accumulate transceiver impairments, rendering an unacceptable system performance. Majority of the technical contributions either assume ideal hardware or inappropriately model hardware impairments which often induce misleading results especially for high data-rate communication systems. We propose statistical mathematical modeling of various hardware impairment (HWI) to characterize their deteriorating effects on the information signal. In addition, we model the aggregate HWI as improper Gaussian signaling (IGS), to fully characterize their asymmetric properties and the self-interfering signal attribute under I/Q imbalance. The proposed model encourages to adopt asymmetric transmission scheme, as opposed to traditional symmetric signaling. First, we present statistical baseband equivalent mathematical models for general MIMO system and two special scenarios of receive and transmit diversity systems under HWI. Then, we express their achievable rate under PGS and IGS transmit schemes. Moreover, we tune the IGS statistical characteristics to maximize the achievable rate. We also present optimal beam-forming/pre-coding and receive combiner vector for multiple-input single-output (MISO) and single-input multiple output (SIMO) systems, which lead to SDNR maximization. Moreover, we propose an adaptive scheme to switch between maximal IGS (MIGS) and PGS transmission based on the described conditions to reduce computational overhead. Subsequently, two case studies are presented. 1) Outage analysis has been carried out for SIMO, under transceiver distortion noise, for two diversity combining schemes 2) The benefits of employing IGS is investigated in full duplex relaying (FDR) suffering from two types of interference, the residual self-interference (RSI) and I/Q distortions. We further optimize the pseudo-variance to compensate the interference impact and improve end-to-end achievable rate. Finally, we validate the analytic expressions through simulation results, to quantify the performance degradation in the absence of ideal transceivers and the gain reaped from adopting IGS scheme compared with PGS scheme.

Future cellular networks, the so-called 5G, are expected to provide explosive data volumes and data rates. To meet such a demand, the research communities are investigating new wireless transmission technologies. One of the most promising candidates is in-band full-duplex communications. These communications are characterized by that a wireless device can simultaneously transmit and receive on the same frequency channel. In-band full-duplex communications have the potential to double the spectral efficiencywhen compared to current half duplex systems. The traditional drawback of full-duplex was the interference that leaks from the own transmitter to its own receiver, the so- called self-interference, which renders the receiving signal unsuitable for communication.However, recent advances in self-interference suppression techniques have provided high cancellation and reduced the self-interference to noise floor levels, which shows full-duplex is becoming a realistic technology component of advanced wireless systems. Although in-band full-duplex promises to double the data rate of existing wireless technologies, its deployment in cellular networks is challenging due to the large number of legacy devices working in half-duplex. A viable introduction in cellular networks is offered by three-node full-duplex deployments, in which only the base stations are full-duplex, whereas the user- or end-devices remain half-duplex. However, in addition to the inherent self-interference, now the interference between users, the user-to-user interference, may become the performance bottleneck, especially as the capability to suppress self-interference improves. Due to this new interference situation, user pairing and frequency channel assignment become of paramount importance, because both mechanisms can help to mitigate the user-to-user interference. It is essential to understand the trade-offs in the performance of full-duplex cellular networks, specially three-node full-duplex, in the design of spectral and energy efficient as well as fair mechanisms. This thesis investigates the design of spectral efficient and fair mechanisms to improve the performance of full-duplex in cellular networks. The novel analysis proposed in this thesis suggests centralized and distributed user pairing, frequency channel assignment and power allocation solutions to maximize the spectral efficiency and fairness in future full-duplex cellular networks. The investigations are based on distributed optimization theory with mixed integer-real variables and novel extensions of Fast-Lipschitz optimization. The analysis sheds lights on two fundamental problems of standard cellular networks, namely the spectral efficiency and fairness maximization, but in the new context of full-duplex communications. The results in this thesis provide important understanding in the role of user pairing, frequency assignment and power allocation, and reveal the special behaviourbetween the legacy self-interference and the new user-to-user interference. This thesis can provide input to the standardization process of full-duplex communications, and have the potential to be used in the implementation of future full-duplex in cellular networks. / <p>QC 20170403</p>