Dual-Polarization OFDM-OQAM Wireless Communication System

In this paper we describe the overall idea and results of a recently proposed radio access technique based on filter bank multicarrier (FBMC) communication system using two orthogonal polarizations: dual-polarization FBMC (DP-FBMC). Using this system we can alleviate the intrinsic interference problem in FBMC systems. This enables use of all the multicarrier techniques used in cyclic-prefix orthogonal frequency-division multiplexing (CP-OFDM) systems for channel equalization, multiple-input/multiple-output (MIMO) processing, etc., without using the extra processing required for conventional FBMC. DP-FBMC also provides other interesting advantages over CP-OFDM and FBMC such as more robustness in multipath fading channels, and more robustness to receiver carrier frequency offset (CFO) and timing offset (TO). For DP-FBMC we propose three different structures based on different multiplexing techniques in time, frequency, and polarization. We will show that one of these structures has exactly the same system complexity and equipment as conventional FBMC. In our simulation results DP-FBMC has better bit error ratio (BER) performance in dispersive channels. Based on these results, DP-FBMC has potential as a promising candidate for future wireless communication systems.Comment: 1.This paper is accepted to be published in IEEE Vehicular Technology Conference (VTC) FALL 2018. 2.In this new submitted version authors have revised the paper based on the VTC FALL reviewers comments. Therefore some typos have fixed and some results have change

Iterative Receiver for MIMO-OFDM System with ICI Cancellation and Channel Estimation

As a multi-carrier modulation scheme, Orthogonal Frequency Division Multiplexing (OFDM) technique can achieve high data rate in frequency-selective fading channels by splitting a broadband signal into a number of narrowband signals over a number of subcarriers, where each subcarrier is more robust to multipath. The wireless communication system with multiple antennas at both the transmitter and receiver, known as multiple-input multiple-output (MIMO) system, achieves high capacity by transmitting independent information over different antennas simultaneously. The combination of OFDM with multiple antennas has been considered as one of most promising techniques for future wireless communication systems. The challenge in the detection of a space-time signal is to design a low-complexity detector, which can efficiently remove interference resulted from channel variations and approach the interference-free bound. The application of iterative parallel interference canceller (PIC) with joint detection and decoding has been a promising approach. However, the decision statistics of a linear PIC is biased toward the decision boundary after the first cancellation stage. In this thesis, we employ an iterative receiver with a decoder metric, which considerably reduces the bias effect in the second iteration, which is critical for the performance of the iterative algorithm. Channel state information is required in a MIMO-OFDM system signal detection at the receiver. Its accuracy directly affects the overall performance of MIMO-OFDM systems. In order to estimate the channel in high-delay-spread environments, pilot symbols should be inserted among subcarriers before transmission. To estimate the channel over all the subcarriers, various types of interpolators can be used. In this thesis, a linear interpolator and a trigonometric interpolator are compared. Then we propose a new interpolator called the multi-tap method, which has a much better system performance. In MIMO-OFDM systems, the time-varying fading channels can destroy the orthogonality of subcarriers. This causes serious intercarrier interference (ICI), thus leading to significant system performance degradation, which becomes more severe as the normalized Doppler frequency increases. In this thesis, we propose a low-complexity iterative receiver with joint frequency- domain ICI cancellation and pilot-assisted channel estimation to minimize the effect of time-varying fading channels. At the first stage of receiver, the interference between adjacent subcarriers is subtracted from received OFDM symbols. The parallel interference cancellation detection with decision statistics combining (DSC) is then performed to suppress the interference from other antennas. By restricting the interference to a limited number of neighboring subcarriers, the computational complexity of the proposed receiver can be significantly reduced. In order to construct the time variant channel matrix in the frequency domain, channel estimation is required. However, an accurate estimation requiring complete knowledge of channel time variations for each block, cannot be obtained. For time- varying frequency-selective fading channels, the placement of pilot tones also has a significant impact on the quality of the channel estimates. Under the assumption that channel variations can be approximated by a linear model, we can derive channel state information (CSI) in the frequency domain and estimate time-domain channel parameters. In this thesis, an iterative low-complexity channel estimation method is proposed to improve the system performance. Pilot symbols are inserted in the transmitted OFDM symbols to mitigate the effect of ICI and the channel estimates are used to update the results of both the frequency domain equalizer and the PICDSC detector in each iteration. The complexity of this algorithm can be reduced because the matrices are precalculated and stored in the receiver when the placement of pilots symbols is fixed in OFDM symbols before transmission. Finally, simulation results show that the proposed MIMO-OFDM iterative receiver can effectively mitigate the effect of ICI and approach the ICI-free performance over time-varying frequency-selective fading channels

Iterative channel estimation techniques for multiple input multiple output orthogonal frequency division multiplexing systems

Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2007Includes bibliographical references (leaves: 77-78)Text in English; Abstract: Turkish and Englishxii, 78 leavesOrthogonal frequency division multiplexing (OFDM) is well-known for its efficient high speed transmission and robustness to frequency-selective fading channels. On the other hand, multiple-input multiple-output (MIMO) antenna systems have the ability to increase capacity and reliability of a wireless communication system compared to single-input single-output (SISO) systems. Hence, the integration of the two technologies has the potential to meet the ever growing demands of future communication systems. In these systems, channel estimation is very crucial to demodulate the data coherently. For a good channel estimation, spectral efficiency and lower computational complexity are two important points to be considered. In this thesis, we explore different channel estimation techniques in order to improve estimation performance by increasing the bandwidth efficiency and reducing the computational complexity for both SISO-OFDM and MIMO-OFDM systems. We first investigate pilot and Expectation-Maximization (EM)-based channel estimation techniques and compare their performances. Next, we explore different pilot arrangements by reducing the number of pilot symbols in one OFDM frame to improve bandwidth efficiency. We obtain the bit error rate and the channel estimation performance for these pilot arrangements. Then, in order to decrase the computational complexity, we propose an iterative channel estimation technique, which establishes a link between the decision block and channel estimation block using virtual subcarriers. We compare this proposed technique with EM-based channel estimation in terms of performance and complexity. These channel estimation techniques are also applied to STBC-OFDM and V-BLAST structured MIMO-OFDM systems. Finally, we investigate a joint EM-based channel estimation and signal detection technique for V-BLAST OFDM system

Adaptive Baseband Pro cessing and Configurable Hardware for Wireless Communication

The world of information is literally at one’s fingertips, allowing access to previously unimaginable amounts of data, thanks to advances in wireless communication. The growing demand for high speed data has necessitated theuse of wider bandwidths, and wireless technologies such as Multiple-InputMultiple-Output (MIMO) have been adopted to increase spectral efficiency.These advanced communication technologies require sophisticated signal processing, often leading to higher power consumption and reduced battery life.Therefore, increasing energy efficiency of baseband hardware for MIMO signal processing has become extremely vital. High Quality of Service (QoS)requirements invariably lead to a larger number of computations and a higherpower dissipation. However, recognizing the dynamic nature of the wirelesscommunication medium in which only some channel scenarios require complexsignal processing, and that not all situations call for high data rates, allowsthe use of an adaptive channel aware signal processing strategy to provide adesired QoS. Information such as interference conditions, coherence bandwidthand Signal to Noise Ratio (SNR) can be used to reduce algorithmic computations in favorable channels. Hardware circuits which run these algorithmsneed flexibility and easy reconfigurability to switch between multiple designsfor different parameters. These parameters can be used to tune the operations of different components in a receiver based on feedback from the digitalbaseband. This dissertation focuses on the optimization of digital basebandcircuitry of receivers which use feedback to trade power and performance. Aco-optimization approach, where designs are optimized starting from the algorithmic stage through the hardware architectural stage to the final circuitimplementation is adopted to realize energy efficient digital baseband hardwarefor mobile 4G devices. These concepts are also extended to the next generation5G systems where the energy efficiency of the base station is improved.This work includes six papers that examine digital circuits in MIMO wireless receivers. Several key blocks in these receiver include analog circuits thathave residual non-linearities, leading to signal intermodulation and distortion.Paper-I introduces a digital technique to detect such non-linearities and calibrate analog circuits to improve signal quality. The concept of a digital nonlinearity tuning system developed in Paper-I is implemented and demonstratedin hardware. The performance of this implementation is tested with an analogchannel select filter, and results are presented in Paper-II. MIMO systems suchas the ones used in 4G, may employ QR Decomposition (QRD) processors tosimplify the implementation of tree search based signal detectors. However,the small form factor of the mobile device increases spatial correlation, whichis detrimental to signal multiplexing. Consequently, a QRD processor capableof handling high spatial correlation is presented in Paper-III. The algorithm and hardware implementation are optimized for carrier aggregation, which increases requirements on signal processing throughput, leading to higher powerdissipation. Paper-IV presents a method to perform channel-aware processingwith a simple interpolation strategy to adaptively reduce QRD computationcount. Channel properties such as coherence bandwidth and SNR are used toreduce multiplications by 40% to 80%. These concepts are extended to usetime domain correlation properties, and a full QRD processor for 4G systemsfabricated in 28 nm FD-SOI technology is presented in Paper-V. The designis implemented with a configurable architecture and measurements show thatcircuit tuning results in a highly energy efficient processor, requiring 0.2 nJ to1.3 nJ for each QRD. Finally, these adaptive channel-aware signal processingconcepts are examined in the scope of the next generation of communicationsystems. Massive MIMO systems increase spectral efficiency by using a largenumber of antennas at the base station. Consequently, the signal processingat the base station has a high computational count. Paper-VI presents a configurable detection scheme which reduces this complexity by using techniquessuch as selective user detection and interpolation based signal processing. Hardware is optimized for resource sharing, resulting in a highly reconfigurable andenergy efficient uplink signal detector

MIMO signal processing in offset-QAM based filter bank multicarrier systems

Next-generation communication systems have to comply with very strict requirements for increased flexibility in heterogeneous environments, high spectral efficiency, and agility of carrier aggregation. This fact motivates research in advanced multicarrier modulation (MCM) schemes, such as filter bank-based multicarrier (FBMC) modulation. This paper focuses on the offset quadrature amplitude modulation (OQAM)-based FBMC variant, known as FBMC/OQAM, which presents outstanding spectral efficiency and confinement in a number of channels and applications. Its special nature, however, generates a number of new signal processing challenges that are not present in other MCM schemes, notably, in orthogonal-frequency-division multiplexing (OFDM). In multiple-input multiple-output (MIMO) architectures, which are expected to play a primary role in future communication systems, these challenges are intensified, creating new interesting research problems and calling for new ideas and methods that are adapted to the particularities of the MIMO-FBMC/OQAM system. The goal of this paper is to focus on these signal processing problems and provide a concise yet comprehensive overview of the recent advances in this area. Open problems and associated directions for future research are also discussed.Peer ReviewedPostprint (author's final draft