Modeling and Analysis of Energy Efficiency in Wireless Handset Transceiver Systems

As wireless communication devices are taking a significant part in our daily life, research steps toward making these devices even faster and smarter are accelerating rapidly. The main limiting factors are energy and power consumption. Many techniques are utilized to increase the battery’s capacity (Ampere per Hour), but that comes with a cost of raising the safety concerns. The other way to increase the battery’s life is to decrease the energy consumption of the devices. In this work, we analyze energy-efficient communications for wireless devices based on an advanced energy consumption model that takes into account a broad range of parameters. The developed model captures relationships between transmission power, transceiver distance, modulation order, channel fading, power amplifier (PA) effects, power control, multiple antennas, as well as other circuit components in the radio frequency (RF) transceiver. Based on the developed model, we are able to identify the optimal modulation order in terms of energy efficiency under different situations (e.g., different transceiver distance, different PA classes and efficiencies, different pulse shape, etc). Furthermore, we capture the impact of system level and network level parameters on the PA energy via peak to average ratio (PAR) and power control. We are also able to identify the impact of multiple antennas at the handset on the energy consumption and the transmitted bit rate for few and many antennas (conventional multiple-input-multiple-output (MIMO) and massive MIMO) at the base station. This work provides an important framework for analyzing energy-efficient communications for different wireless systems ranging from cellular networks to wireless internet of things

Spectral-energy efficiency trade-off for next-generation wireless communication systems

The data traffic in cellular networks has had and will experience a rapid exponential rise. Therefore, it is essential to innovate a new cellular architecture with advanced wireless technologies that can offer more capacity and enhanced spectral efficiency to manage the exponential data traffic growth. Managing such mass data traffic, however, brings up another challenge of increasing energy consumption. This is because it contributes into a growing fraction of the carbon dioxide (CO2) emission which is a global concern today due to its negative impact on the environment. This has resulted in creating a new paradigm shift towards both spectral and energy efficient orientated design for the next-generation wireless access networks. Acquiring both improved energy efficiency and spectral efficiency has, nonetheless, shown to be a difficult goal to achieve as it seems improving one is at the detriment to the other. Therefore, the trade-off between the spectral and energy efficiency is of paramount importance to assess the energy consumption in a wireless communication system required to attain a specific spectral efficiency. This thesis looks into this problem. It studies the spectral-energy efficiency tradeoff for some of the emerging wireless communication technologies which are seen as potential candidates for the fifth generation (5G) mobile cellular system. The focus is on the orthogonal frequency division multiple access (OFDMA), mobile femtocell (MFemtocell), cognitive radio (CR), and the spatial modulation (SM). Firstly, the energy-efficient resource allocation scheme for multi-user OFDMA (MU-OFDMA) system is studied. The spectral-energy efficiency trade-off is analysed under the constraint of maintaining the fairness among users. The energy-efficient optimisation problem has been formulated as integer fractional programming. We then apply an iterative method to simplify the problem to an integer linear programming (ILP) problem. Secondly, the spectral and energy efficiency for a cellular system with MFemtocell deployment is investigated using different resource partitioning schemes. Femtocells are low range, low power base stations (BSs) that improve the coverage inside a home or office building. MFemtocell adopts the femtocell solution to be deployed in public transport and emergency vehicles. Closed-form expressions for the relationships between the spectral and energy efficiency are derived for a single-user (SU) MFemtocell network. We also study the spectral efficiency for MU-MFemtocells with two opportunistic scheduling schemes. Thirdly, the spectral-energy efficiency trade-off for CR networks is analysed at both SU and MU CR systems against varying signal-to-noise ratio (SNR) values. CR is an innovative radio device that aims to utilise the spectrum more efficiently by opportunistically exploiting underutilised licensed spectrum. For the SU system, we study the required energy to achieve a specific spectral efficiency for a CR channel under two different types of power constraints in different fading environments. In this scenario, interference constraint at the primary receiver (PR) is also considered to protect the PR from harmful interference. At the system level, we study the spectral and energy efficiency for a CR network that shares the spectrum with an indoor network. Adopting the extreme-value theory, we are able to derive the average spectral efficiency of the CR network. Finally, we propose two innovative schemes to enhance the capability of (SM). SM is a recently developed technique that is employed for a low complexity multipleinput multiple-output (MIMO) transmission. The first scheme can be applied for SU MIMO (SU-MIMO) to offer more degrees of freedom than SM. Whereas the second scheme introduces a transmission structure by which the SM is adopted into a downlink MU-MIMO system. Unlike SM, both proposed schemes do not involve any restriction into the number of transmit antennas when transmitting signals. The spectral-energy efficiency trade-off for the MU-SM in the massive MIMO system is studied. In this context, we develop an iterative energy-efficient water-filling algorithm to optimises the transmit power and achieve the maximum energy efficiency for a given spectral efficiency. In summary, the research presented in this thesis reveals mathematical tools to analysis the spectral and energy efficiency for wireless communications technologies. It also offers insight to solve optimisation problems that belong to a class of problems with objectives of enhancing the energy efficiency

Grant-Free Massive MTC-Enabled Massive MIMO: A Compressive Sensing Approach

A key challenge of massive MTC (mMTC), is the joint detection of device activity and decoding of data. The sparse characteristics of mMTC makes compressed sensing (CS) approaches a promising solution to the device detection problem. However, utilizing CS-based approaches for device detection along with channel estimation, and using the acquired estimates for coherent data transmission is suboptimal, especially when the goal is to convey only a few bits of data. First, we focus on the coherent transmission and demonstrate that it is possible to obtain more accurate channel state information by combining conventional estimators with CS-based techniques. Moreover, we illustrate that even simple power control techniques can enhance the device detection performance in mMTC setups. Second, we devise a new non-coherent transmission scheme for mMTC and specifically for grant-free random access. We design an algorithm that jointly detects device activity along with embedded information bits. The approach leverages elements from the approximate message passing (AMP) algorithm, and exploits the structured sparsity introduced by the non-coherent transmission scheme. Our analysis reveals that the proposed approach has superior performance compared to application of the original AMP approach.Comment: Submitted to IEEE Transactions on Communication

Performance Enhancement Using NOMA-MIMO for 5G Networks

The integration of MIMO and NOMA technologies addresses key challenges in 5G and beyond, such as connectivity, latency, and dependability. However, resolving these issues, especially in MIMO-enabled 5G networks, required additional research. This involved optimizing parameters like bit error rate, downlink spectrum efficiency, average capacity rate, and uplink transmission outage probability. The model employed Quadrature Phase Shift Keying modulation on selected frequency channels, accommodating diverse user characteristics. Evaluation showed that MIMO-NOMA significantly improved bit error rate and transmitting power for the best user in download transmission. For uplink transmission, there was an increase in the average capacity rate and a decrease in outage probability for the best user. Closed-form formulas for various parameters in both downlink and uplink NOMA, with and without MIMO, were derived. Overall, adopting MIMO-NOMA led to a remarkable performance improvement for all users, even in challenging conditions like interference or fading channels

Cross-Layer Optimization for Power-Efficient and Robust Digital Circuits and Systems

With the increasing digital services demand, performance and power-efficiency become vital requirements for digital circuits and systems. However, the enabling CMOS technology scaling has been facing significant challenges of device uncertainties, such as process, voltage, and temperature variations. To ensure system reliability, worst-case corner assumptions are usually made in each design level. However, the over-pessimistic worst-case margin leads to unnecessary power waste and performance loss as high as 2.2x. Since optimizations are traditionally confined to each specific level, those safe margins can hardly be properly exploited. To tackle the challenge, it is therefore advised in this Ph.D. thesis to perform a cross-layer optimization for digital signal processing circuits and systems, to achieve a global balance of power consumption and output quality. To conclude, the traditional over-pessimistic worst-case approach leads to huge power waste. In contrast, the adaptive voltage scaling approach saves power (25% for the CORDIC application) by providing a just-needed supply voltage. The power saving is maximized (46% for CORDIC) when a more aggressive voltage over-scaling scheme is applied. These sparsely occurred circuit errors produced by aggressive voltage over-scaling are mitigated by higher level error resilient designs. For functions like FFT and CORDIC, smart error mitigation schemes were proposed to enhance reliability (soft-errors and timing-errors, respectively). Applications like Massive MIMO systems are robust against lower level errors, thanks to the intrinsically redundant antennas. This property makes it applicable to embrace digital hardware that trades quality for power savings.Comment: 190 page