Semiblind Channel Estimation and Data Detection for OFDM Systems With Optimal Pilot Design

This paper considers semiblind channel estimation and data detection for orthogonal frequency-division multiplexing (OFDM) over frequency-selective fading channels. We show that the samples of an OFDM symbol are jointly complex Gaussian distributed, where the mean and covariance are determined by the locations and values of fixed pilot symbols. We exploit this distribution to derive a novel maximum-likelihood (ML) semiblind gradient-descent channel estimator. By exploiting the channel impulse response (CIR) statistics, we also derive a semiblind data detector for both Rayleigh and Ricean fading channels. Furthermore, we develop an enhanced data detector, which uses the estimator error statistics to mitigate the effect of channel estimation errors. Efficient implementation of both the semiblind and the improved data detectors is provided via sphere decoding and nulling-canceling detection. We also derive the Cramér-Rao bound (CRB) and design optimal pilots by minimizing the CRB. Our proposed channel estimator and data detector exhibit high bandwidth efficiency (requiring only a few pilot symbols), achieve the CRB, and also nearly reach the performance of an ideal reference receiver

Performance enhancement for LTE and beyond systems

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyWireless communication systems have undergone fast development in recent years. Based on GSM/EDGE and UMTS/HSPA, the 3rd Generation Partnership Project (3GPP) specified the Long Term Evolution (LTE) standard to cope with rapidly increasing demands, including capacity, coverage, and data rate. To achieve this goal, several key techniques have been adopted by LTE, such as Multiple-Input and Multiple-Output (MIMO), Orthogonal Frequency-Division Multiplexing (OFDM), and heterogeneous network (HetNet). However, there are some inherent drawbacks regarding these techniques. Direct conversion architecture is adopted to provide a simple, low cost transmitter solution. The problem of I/Q imbalance arises due to the imperfection of circuit components; the orthogonality of OFDM is vulnerable to carrier frequency offset (CFO) and sampling frequency offset (SFO). The doubly selective channel can also severely deteriorate the receiver performance. In addition, the deployment of Heterogeneous Network (HetNet), which permits the co-existence of macro and pico cells, incurs inter-cell interference for cell edge users. The impact of these factors then results in significant degradation in relation to system performance. This dissertation aims to investigate the key techniques which can be used to mitigate the above problems. First, I/Q imbalance for the wideband transmitter is studied and a self-IQ-demodulation based compensation scheme for frequencydependent (FD) I/Q imbalance is proposed. This combats the FD I/Q imbalance by using the internal diode of the transmitter and a specially designed test signal without any external calibration instruments or internal low-IF feedback path. The instrument test results show that the proposed scheme can enhance signal quality by 10 dB in terms of image rejection ratio (IRR). In addition to the I/Q imbalance, the system suffers from CFO, SFO and frequency-time selective channel. To mitigate this, a hybrid optimum OFDM receiver with decision feedback equalizer (DFE) to cope with the CFO, SFO and doubly selective channel. The algorithm firstly estimates the CFO and channel frequency response (CFR) in the coarse estimation, with the help of hybrid classical timing and frequency synchronization algorithms. Afterwards, a pilot-aided polynomial interpolation channel estimation, combined with a low complexity DFE scheme, based on minimum mean squared error (MMSE) criteria, is developed to alleviate the impact of the residual SFO, CFO, and Doppler effect. A subspace-based signal-to-noise ratio (SNR) estimation algorithm is proposed to estimate the SNR in the doubly selective channel. This provides prior knowledge for MMSE-DFE and automatic modulation and coding (AMC). Simulation results show that this proposed estimation algorithm significantly improves the system performance. In order to speed up algorithm verification process, an FPGA based co-simulation is developed. Inter-cell interference caused by the co-existence of macro and pico cells has a big impact on system performance. Although an almost blank subframe (ABS) is proposed to mitigate this problem, the residual control signal in the ABS still inevitably causes interference. Hence, a cell-specific reference signal (CRS) interference cancellation algorithm, utilizing the information in the ABS, is proposed. First, the timing and carrier frequency offset of the interference signal is compensated by utilizing the cross-correlation properties of the synchronization signal. Afterwards, the reference signal is generated locally and channel response is estimated by making use of channel statistics. Then, the interference signal is reconstructed based on the previous estimate of the channel, timing and carrier frequency offset. The interference is mitigated by subtracting the estimation of the interference signal and LLR puncturing. The block error rate (BLER) performance of the signal is notably improved by this algorithm, according to the simulation results of different channel scenarios. The proposed techniques provide low cost, low complexity solutions for LTE and beyond systems. The simulation and measurements show good overall system performance can be achieved

Model classification-and-selection assisted robust receiver for OFDM systems

This paper devises a robust receiver for OFDM systems in the presence of residual timing offsets and unknown channel prior information. The proposed receiver constructs typical receiver models and resorts to the model selection technique to choose the best-matched receiver model to improve the channel estimation and signal detection. The typical receiver models are classified by considering the channel delay spread and the level of timing offset. Based on the receiver model selected by the Bayesian model selection algorithm, the channel length and timing offset parameters in the receiver model can provide the effective channel statistical information to make the channel estimator adapt to the altered circumstances and thus more accurate. Furthermore, the effective interference variance parameters in the selected receiver model are used to enhance the channel estimation and refine the soft symbol detection. The simulation results show that the proposed receiver achieves a significant performance gain compared to the existing methods. It is also shown that the proposed scheme makes the receiver robust to the diverse channel conditions and the timing offset states at a cost of the only a moderate increase in complexity

Multiuser MIMO-OFDM for Next-Generation Wireless Systems

This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

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

CHANNEL ESTIMATION DESIGN OF MIMOOFDM SYSTEMS USING MMSE FOR IEEE 802.11N WLAN STANDARD

IEEE 802.11n is the latest development of IEEE 802.11 WLAN communication standard that provides higher significant throughput than IEEE 802.11a/g. With various of transmission channels in wireless communication, has decreased performance of the receiver antennas caused by noise interference and fading channel. Hence, there is a need to analyze channel estimation method to estimate and discover the real condition of channel information between transmitter and receiver for IEEE 802.11n WLAN communication standard. This research simulated the channel estimator using minimum mean squared error (MMSE) algorithm in MIMOOFDM systems with 2x2 and 2x4 schemes. Rectangular shaping filter assumption in time domain is used for the channel approximation due to the multipath Rayleigh fading channel distribution. System performance value is shown in channel impulse response of Tx transmitter to Rx receiver. The simulation results indicate that channel estimator has been working on purpose in MIMO-OFDM system with antenna scheme of 2x2 and 2x4 as well