Cooperative Distributed Transmission and Reception

In telecommunications, a cooperative scheme refers to a method where two or more users share or combine their information in order to increase diversity gain or power gain. In contrast to conventional point-to-point communications, cooperative communications allow different users in a wireless network to share resources so that instead of maximizing the performance of its own link, each user collaborates with its neighbours to achieve an overall improvement in performance. In this dissertation, we consider different models for transmission and reception and explore cooperative techniques that increase the reliability and capacity gains in wireless networks, with consideration to practical issues such as channel estimation errors and backhaul constraints. This dissertation considers the design and performance of cooperative communication techniques. Particularly, the first part of this dissertation focuses on the performance comparison between interference alignment and opportunistic transmission for a 3-user single-input single- output (SISO) interference channel in terms of average sum rate in the presence of channel estimation errors. In the case of interference alignment, channel estimation errors cause interference leakage which consequently results in a loss of achievable rate. In the case of opportunistic transmission, channel estimation errors result in a non-zero probability of incorrectly choosing the node with the best channel. The effect of these impairments is quantified in terms of the achievable average sum rate of these transmission techniques. Analysis and numerical examples show that SISO interference alignment can achieve better average sum rate with good channel estimates and at high SNR whereas opportunistic transmission provides better performance at low SNR and/or when the channel estimates are poor. We next considers the problem of jointly decoding binary phase shift keyed (BPSK) messages from a single distant transmitter to a cooperative receive cluster connected by a local area network (LAN). An approximate distributed receive beamforming algorithm is proposed based on the exchange of coarsely- quantized observations among some or all of the nodes in the receive cluster. By taking into account the differences in channel quality across the receive cluster, the quantized information from other nodes in the receive cluster can be appropriately combined with locally unquantized information to form an approximation of the ideal receive beamformer decision statistic. The LAN throughput requirements of this technique are derived as a function of the number of participating nodes in the receive cluster, the forward link code rate, and the quantization parameters. Using information-theoretic analysis and simulations of an LDPC coded system in fading channels, numerical results show that the performance penalty (in terms of outage probability and block error rate) due to coarse quantization is small in the low SNR regimes enabled by cooperative distributed reception. An upper/lower bound approximation is derived based on a circle approximation in the channel magnitude domain which provides a pretty fast way to compute the outage probability performance for a system with arbitrary number of receivers at a given SNR. In the final part of this dissertation, we discuss the distributed reception technique with higher- order modulation schemes in the forward link. The extension from BPSK to QPSK is straightforward and is studied in the second part of this dissertation. The extension to 8PSK, 4PAM and 16QAM forward links, however, is not trivial. For 8PSK, two techniques are proposed: pseudobeamforming and 3-bit belief combining where the first one is intuitive and turns out to be suboptimal,the latter is optimal in terms of outage probability performance. The idea of belief combining can be applied to the 4PAM and 16QAM and it is shown that better/finer quantizer design can further improve the block error rate performance. Information-theoretic analysis and numerical results are provided to show that significant reliability and SNR gains can be achieved by using the proposed schemes

JamLab: Augmenting Sensornet Testbeds with Realistic and Controlled Interference Generation

Radio interference drastically affects the performance of sensor-net communications, leading to packet loss and reduced energy-efficiency. As an increasing number of wireless devices operates on the same ISM frequencies, there is a strong need for understanding and debugging the performance of existing sensornet protocols under interference. Doing so requires a low-cost flexible testbed infrastructure that allows the repeatable generation of a wide range of interference patterns. Unfortunately, to date, existing sensornet testbeds lack such capabilities, and do not permit to study easily the coexistence problems between devices sharing the same frequencies. This paper addresses the current lack of such an infrastructure by using off-the-shelf sensor motes to record and playback interference patterns as well as to generate customizable and repeat-able interference in real-time. We propose and develop JamLab: a low-cost infrastructure to augment existing sensornet testbeds with accurate interference generation while limiting the overhead to a simple upload of the appropriate software. We explain how we tackle the hardware limitations and get an accurate measurement and regeneration of interference, and we experimentally evaluate the accuracy of JamLab with respect to time, space, and intensity. We further use JamLab to characterize the impact of interference on sensornet MAC protocols

Simulations of Implementation of Advanced Communication Technologies

Wireless communication systems have seen significant advancements with the introduction of 3G, 4G, and 5G mobile standards. Since the simulation of entire systems is complex and may not allow evaluation of the impact of individual techniques, this thesis presents techniques and results for simulating the performance of advanced signaling techniques used in 3G, 4G, and 5G systems, including Code division multiple access (CDMA), Multiple Input Multiple Output (MIMO) systems, and Low-Density Parity Check (LDPC) codes. One implementation issue that is explored is the use of quantized Analog to Digital Converter (ADC) outputs and their impact on system performance. Code division multiple access (CDMA) is a popular wireless technique, but its effectiveness is limited by factors such as multiple access interference (MAI) and the near far effect (NFE). The joint effect of sampling and quantization on the analog-digital converter (ADC) at the receiver\u27s front end has also been evaluated for different quantization bits. It has been demonstrated that 4 bits is the minimum ADC resolution sensitivity required for a reliable connection for a quantized signal with 3- and 6-dB power levels in noisy and interference-prone environments. The demand for high data rate, reliable transmission, low bit error rate, and maximum transmission with low power has increased in wireless systems. Multiple Input Multiple Output (MIMO) systems with multiple antennas at both the transmitter and receiver side can meet these requirements by exploiting diversity and multipath propagation. The focus of MIMO systems is on improving reliability and maximizing throughput. Performance analysis of single input single output (SISO), single input multiple output (SIMO), multiple input single output (MISO), and MIMO systems is conducted using Alamouti space time block code (STBC) and Maximum Ratio Combining (MRC) technique used for transmit and receive diversity for Rayleigh fading channel under AWGN environment for BPSK and QPSK modulation schemes. Spatial Multiplexing (SM) is used to enhance spectral efficiency without additional bandwidth and power requirements. Minimum mean square error (MMSE) method is used for signal detection at the receiver end due to its low complexity and better performance. The performance of MIMO SM technique is compared for different antenna configurations and modulation schemes, and the MMSE detector is employed at the receiving end. Advanced error correction techniques for channel coding are necessary to meet the demand for Mobile Internet in 5G wireless communications, particularly for the Internet of Things. Low Density Parity Check (LDPC) codes are used for error correction in 5G, offering high coding gain, high throughput, low latency, low power dissipation, low complexity, and rate compatibility. LDPC codes use base matrices of 5G New Radio (NR) for LDPC encoding, and a soft decision decoding algorithm is used for efficient Frame Error Rate (FER) performance. The performance of LDPC codes is assessed using a soft decision decoding layered message passing algorithm, with BPSK modulation and AWGN channel. Furthermore, the effects of quantization on LDPC codes are analyzed for both small and large numbers of quantization bits