Detection for 5G-NOMA: An Online Adaptive Machine Learning Approach

Non-orthogonal multiple access (NOMA) has emerged as a promising radio access technique for enabling the performance enhancements promised by the fifth-generation (5G) networks in terms of connectivity, low latency, and high spectrum efficiency. In the NOMA uplink, successive interference cancellation (SIC) based detection with device clustering has been suggested. In the case of multiple receive antennas, SIC can be combined with the minimum mean-squared error (MMSE) beamforming. However, there exists a tradeoff between the NOMA cluster size and the incurred SIC error. Larger clusters lead to larger errors but they are desirable from the spectrum efficiency and connectivity point of view. We propose a novel online learning based detection for the NOMA uplink. In particular, we design an online adaptive filter in the sum space of linear and Gaussian reproducing kernel Hilbert spaces (RKHSs). Such a sum space design is robust against variations of a dynamic wireless network that can deteriorate the performance of a purely nonlinear adaptive filter. We demonstrate by simulations that the proposed method outperforms the MMSE-SIC based detection for large cluster sizes.Comment: Accepted at ICC 201

milliProxy: a TCP Proxy Architecture for 5G mmWave Cellular Systems

TCP is the most widely used transport protocol in the internet. However, it offers suboptimal performance when operating over high bandwidth mmWave links. The main issues introduced by communications at such high frequencies are (i) the sensitivity to blockage and (ii) the high bandwidth fluctuations due to Line of Sight (LOS) to Non Line of Sight (NLOS) transitions and vice versa. In particular, TCP has an abstract view of the end-to-end connection, which does not properly capture the dynamics of the wireless mmWave link. The consequence is a suboptimal utilization of the available resources. In this paper we propose a TCP proxy architecture that improves the performance of TCP flows without any modification at the remote sender side. The proxy is installed in the Radio Access Network, and exploits information available at the gNB in order to maximize throughput and minimize latency.Comment: 7 pages, 6 figures, 2 tables, presented at the 2017 51st Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 201

Channel estimation and tracking algorithms for vehicle to vehicle communications

The vehicle-to-vehicle (V2V) communications channels are highly time-varying, making reliable communication difficult. This problem is particularly challenging because the standard of the V2V communications (IEEE 802.11p standard) is based on the WLAN IEEE 802.11a standard, which was designed for indoor, relatively stationary channels; so the IEEE 802.11p standard is not customized for outdo or, highly mobile non-stationary channels. In this thesis,We propose Channel estimation and tracking algorithms that are suitable for highly-time varying channels. The proposed algorithms utilize the finite alphabet property of the transmitted symbol, time domain truncation, decision-directed as well as pilot information. The proposed algorithm s improve the overall system performance in terms of bit error rates, enabling the system to achieve higher data rates and larger packet lengths at high relative velocities. Simulation results show that the proposed algorithms achieve improved performance for all the V2V channel models with different velocities, and for different modulation schemes and packet sizes as compared to the conventional least squares and other previously proposed channel estimation techniques for V2V channels

Transcranial Electric Stimulation Entrains Cortical Neuronal Populations in Rats

Low intensity electric fields have been suggested to affect the ongoing neuronal activity in vitro and in human studies. However, the physiological mechanism of how weak electrical fields affect and interact with intact brain activity is not well understood. We performed in vivo extracellular and intracellular recordings from the neocortex and hippocampus of anesthetized rats and extracellular recordings in behaving rats. Electric fields were generated by sinusoid patterns at slow frequency (0.8, 1.25 or 1.7 Hz) via electrodes placed on the surface of the skull or the dura. Transcranial electric stimulation (TES) reliably entrained neurons in widespread cortical areas, including the hippocampus. The percentage of TES phase-locked neurons increased with stimulus intensity and depended on the behavioral state of the animal. TES-induced voltage gradient, as low as 1 mV/mm at the recording sites, was sufficient to phase-bias neuronal spiking. Intracellular recordings showed that both spiking and subthreshold activity were under the combined influence of TES forced fields and network activity. We suggest that TES in chronic preparations may be used for experimental and therapeutic control of brain activity

Low Complexity Wireless Communication Digital Baseband Design

abstract: This thesis addresses two problems in digital baseband design of wireless communication systems, namely, those in Internet of Things (IoT) terminals that support long range communications and those in full-duplex systems that are designed for high spectral efficiency. IoT terminals for long range communications are typically based on Orthogonal Frequency-Division Multiple Access (OFDMA) and spread spectrum technologies. In order to design an efficient baseband architecture for such terminals, the workload profiles of both systems are analyzed. Since frame detection unit has by far the highest computational load, a simple architecture that uses only a scalar datapath is proposed. To optimize for low energy consumption, application-specific instructions that minimize register accesses and address generation units for streamlined memory access are introduced. Two parameters, namely, correlation window size and threshold value, affect the detection probability, the false alarm probability and hence energy consumption. Next, energy-optimal operation settings for correlation window size and threshold value are derived for different channel conditions. For both good and bad channel conditions, if target signal detection probability is greater than 0.9, the baseband processor has the lowest energy when the frame detection algorithm uses the longest correlation window and the highest threshold value. A full-duplex system has high spectral efficiency but suffers from self-interference. Part of the interference can be cancelled digitally using equalization techniques. The cancellation performance and computation complexity of the competing equalization algorithms, namely, Least Mean Square (LMS), Normalized LMS (NLMS), Recursive Least Square (RLS) and feedback equalizers based on LMS, NLMS and RLS are analyzed, and a trade-off between performance and complexity established. NLMS linear equalizer is found to be suitable for resource-constrained mobile devices and NLMS decision feedback equalizer is more appropriate for base stations that are not energy constrained.Dissertation/ThesisMasters Thesis Electrical Engineering 201

Network-coded NOMA with antenna selection for the support of two heterogeneous groups of users

The combination of Non-Orthogonal Multiple Access (NOMA) and Transmit Antenna Selection (TAS) techniques has recently attracted significant attention due to the low cost, low complexity and high diversity gains. Meanwhile, Random Linear Coding (RLC) is considered to be a promising technique for achieving high reliability and low latency in multicast communications. In this paper, we consider a downlink system with a multi-antenna base station and two multicast groups of single-antenna users, where one group can afford to be served opportunistically, while the other group consists of comparatively low power devices with limited processing capabilities that have strict Quality of Service (QoS) requirements. In order to boost reliability and satisfy the QoS requirements of the multicast groups, we propose a cross-layer framework including NOMAbased TAS at the physical layer and RLC at the application layer. In particular, two low complexity TAS protocols for NOMA are studied in order to exploit the diversity gain and meet the QoS requirements. In addition, RLC analysis aims to facilitate heterogeneous users, such that, sliding window based sparse RLC is employed for computational restricted users, and conventional RLC is considered for others. Theoretical expressions that characterize the performance of the proposed framework are derived and verified through simulation results