Multiple-Access Technology of Choice In 3GPP LTE

Third-Generation Partnership Project (3GPP) standardizes an Evolved UMTS Terrestrial Radio Access Network (E-UTRAN) as air interface in its release 8 LTE. Orthogonal Frequency Division Multiple Access(OFDMA) and Single Carrier-Frequency Division Multiple Access(SC-FDMA)are key technologies for the air interface of mobile broadband systems.It is evident that mobile broadband access technologies are reaching a commonality in the air interface and networking architecture; they are being converged to an IP-based network architecture with OFDMA based air interface technology. The air interface of E-UTRAN is based on OFDMA in downlink and SC-FDMA in the uplink, making it possible to efficiently utilize bandwidth due to the orthogonally between sub-carriers and by assigning subsets of sub-carriers to individual users which allows for simultaneous data rate transmission from several users and differentiated quality of service for each user. In this paper, wehighlight the technologies behindOFDMA and SC-FDMA and also carry out performance comparison of the two air interface technologies. We brieflydescribe the 3GPP LTE standard, and its implementation using OFDMA and SC-FDMA technology

PAPR reduction in OFDM communications with generalized discrete Fourier transform

The main advantage of Generalized Discrete Fourier Transform (GDFT) is its ability to design a wide selection of constant modulus orthogonal code sets, based on the desired performance metrics mimicking the engineering specs of interest. One of the main drawbacks of Orthogonal Frequency Division Multiplexing (OFDM) systems is the high Peak to Average Power Ratio (PAPR) value which is directly related to power consumption of the system. Discrete Fourier Transform (DFT) spread OFDM technology, also known as Single Carrier Frequency Division Multiple Access (SCFDMA), which has a lower PAPR value, is used for uplink channel. In this thesis, the PAPR of DFT spread OFDM was further decreased by using a GDFT concept. The performance improvements of GDFT based PAPR reduction for various SCFDMA communications scenarios were evaluated by simulations. Performance simulation results showed that PAPR efficiency of SCFDMA systems for Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK) and 16 Quadrature Amplitude Modulation (16-QAM), digital modulation techniques are increased

A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels

In this paper, we establish a general framework on the reduced dimensional channel state information (CSI) estimation and pre-beamformer design for frequency-selective massive multiple-input multiple-output MIMO systems employing single-carrier (SC) modulation in time division duplex (TDD) mode by exploiting the joint angle-delay domain channel sparsity in millimeter (mm) wave frequencies. First, based on a generic subspace projection taking the joint angle-delay power profile and user-grouping into account, the reduced rank minimum mean square error (RR-MMSE) instantaneous CSI estimator is derived for spatially correlated wideband MIMO channels. Second, the statistical pre-beamformer design is considered for frequency-selective SC massive MIMO channels. We examine the dimension reduction problem and subspace (beamspace) construction on which the RR-MMSE estimation can be realized as accurately as possible. Finally, a spatio-temporal domain correlator type reduced rank channel estimator, as an approximation of the RR-MMSE estimate, is obtained by carrying out least square (LS) estimation in a proper reduced dimensional beamspace. It is observed that the proposed techniques show remarkable robustness to the pilot interference (or contamination) with a significant reduction in pilot overhead

General Framework and Novel Transceiver Architecture based on Hybrid Beamforming for NOMA in Massive MIMO Channels

Massive MIMO and non-orthogonal multiple access (NOMA) are crucial methods for future wireless systems as they provide many advantages over conventional systems. Power domain NOMA methods are investigated in massive MIMO systems, whereas there is little work on integration of code domain NOMA and massive MIMO which is the subject of this study. We propose a general framework employing user-grouping based hybrid beamforming architecture for mm-wave massive MIMO systems where NOMA is considered as an intra-group process. It is shown that classical receivers of sparse code multiple access (SCMA) and multi-user shared access (MUSA) can be directly adapted. Additionally, a novel receiver architecture which is an improvement over classical one is proposed for uplink MUSA. This receiver makes MUSA preferable over SCMA for uplink transmission with lower complexity. We provide a lower bound on achievable information rate (AIR) as a performance measure. We show that code domain NOMA schemes outperform conventional methods with very limited number of radio frequency (RF) chains where users are spatially close to each other. Furthermore, we provide an analysis in terms of bit-error rate and AIR under different code length and overloading scenarios for uplink transmission where flexible structure of MUSA is exploited.Comment: Partially presented at IEEE ICC 2020 Workshop on NOMA for 5G and Beyond and to be submitted to IEEE Transactions on Communication

Waveform Design for 5G and beyond Systems

5G traffic has very diverse requirements with respect to data rate, delay, and reliability. The concept of using multiple OFDM numerologies adopted in the 5G NR standard will likely meet these multiple requirements to some extent. However, the traffic is radically accruing different characteristics and requirements when compared with the initial stage of 5G, which focused mainly on high-speed multimedia data applications. For instance, applications such as vehicular communications and robotics control require a highly reliable and ultra-low delay. In addition, various emerging M2M applications have sparse traffic with a small amount of data to be delivered. The state-of-the-art OFDM technique has some limitations when addressing the aforementioned requirements at the same time. Meanwhile, numerous waveform alternatives, such as FBMC, GFDM, and UFMC, have been explored. They also have their own pros and cons due to their intrinsic waveform properties. Hence, it is the opportune moment to come up with modification/variations/combinations to the aforementioned techniques or a new waveform design for 5G systems and beyond. The aim of this Special Issue is to provide the latest research and advances in the field of waveform design for 5G systems and beyond

Implementation of Deep-Learning-Based CSI Feedback Reporting on 5G NR-Compliant Link-Level Simulator

Advances in machine learning have widened the range of its applications in many fields. In particular, deep learning has attracted much interest for its ability to provide solutions where the derivation of a rigorous mathematical model of the problem is troublesome. Our interest was drawn to the application of deep learning for channel state information feedback reporting, a crucial problem in frequency division duplexing (FDD) 5G networks, where knowledge of the channel characteristics is fundamental to exploiting the full potential of multiple-input multiple-output (MIMO) systems. We designed a framework adopting a 5G New Radio convolutional neural network, called NR-CsiNet, with the aim of compressing the channel matrix experienced by the user at the receiver side and then reconstructing it at the transmitter side. In contrast to similar solutions, our framework is based on a 5G New Radio fully compliant simulator, thus implementing a channel generator based on the latest 3GPP 3-D channel model. Moreover, realistic 5G scenarios are considered by including multi-receiving antenna schemes and noisy downlink channel estimation. Simulations were carried out to analyze and compare the performance with current feedback reporting schemes, showing promising results for this approach from the point of view of the block error rate and throughput of the 5G data channel

Phase noise effects on OFDM : analysis and mitigation

Orthogonal frequency division multiplexing (OFDM) is a promising technique which has high spectrum efficiency and the robustness against channel frequency selectivity. One drawback of OFDM is its sensitivity to phase noise. It has been shown that even small phase noise leads to significant performance loss of OFDM. Therefore, phase noise effects on OFDM systems need to be analyzed and methods be provided to its mitigation. Motivated by what have been proposed in the literature, the exact signal to interference plus noise ratio (SINR) is derived in this dissertation for arbitrary phase noise levels. In a multiple access environment with multiple phase noise, the closed form of bit error rate (BER) performance is derived as a function of phase noise parameters. Due to the detrimental effects of phase noise on OFDM, phase noise mitigation is quite necessary. Several schemes are proposed to mitigate both single and multiple phase noise. It is shown that, while outperforming conventional methods, these schemes have the performance close to no-phase-noise case. Two general approaches are presented which extend the conventional schemes proposed in the literature, making them special cases of these general approaches. Moreover, different implementation techniques are also presented. Analytical and numerical results are provided to compare the performance of these migitation approaches and implementation techniques. Similar to OFDM, an OFDM system with multiple antennas, i.e., Multiple Input. Multiple Output (MIMO)-OFDM, also suffer severe performance degradation due to phase noise, and what have been proposed in the literature may not be applicable to MIMO-OFDM. Therefore, a new scheme is proposed to mitigate phase noise for MIMO-OFDM, which provides significant performance gains over systems without phase noise mitigation. This scheme provides a very simple structure and achieves adequate performance with high spectrum efficiency, which makes it very attractive for practical implementations

Intelligent genetic algorithms for next-generation broadband multi-carrier CDMA wireless networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This dissertation proposes a novel intelligent system architecture for next-generation broadband multi-carrier CDMA wireless networks. In our system, two novel and similar intelligent genetic algorithms, namely Minimum Distance guided GAs (MDGAs) are invented for both peak-to-average power ratio (PAPR) reduction at the transmitter side and multi-user detection (MUD) at the receiver side. Meanwhile, we derive a theoretical BER performance analysis for the proposed MC-CDMA system in A WGN channel. Our analytical results show that the theoretical BER performance of synchronized MC-CDMA system is the same as that of the synchronized DS-CDMA system which is also used as a theoretical guidance of our novel MUD receiver design. In contrast to traditional GAs, our MDGAs start with a balanced ratio of exploration and exploitation which is maintained throughout the process. In our algorithms, a new replacement strategy is designed which increases significantly the convergence rate and reduces dramatically computational complexity as compared to the conventional GAs. The simulation results demonstrate that, if compared to those schemes using exhaustive search and traditional GAs, (1) our MDGA-based P APR reduction scheme achieves 99.52% and 50+% reductions in computational complexity, respectively; (2) our MDGA-based MUD scheme achieves 99.54% and 50+% reductions in computational complexity, respectively. The use of one core MDGA solution for both issues can ease the hardware design and dramatically reduce the implementation cost in practice