High data rates give rise to frequency-selective channel effects. Space-time multiplexing and/or coding offer attractive means of combating fading, and boosting capacity of multi-antenna communications. As the number of antennas increases, channel estimation becomes challenging because the number of unknowns increases, and the power is split at the transmitter. In this paper, we design a low complexity optimal training scheme for block transmissions over frequency-selective channels with multiple antennas. The optimality in designing our training schemes consists of maximizing a lower bound on the average capacity that is shown to be equivalent to minimizing the mean-square error of the linear channel estimator. Simulation results confirm our theoretical analysis.

Abstract—This paper presents general classes of optimal training signals for estimation of frequency-selective channels in MIMO OFDM systems. Basic properties of the discrete Fourier transform are used to derive the optimal training signals which minimize the channel estimation mean square error. Both single and multiple OFDM training symbols are considered. Several optimal pilot tone allocations among the transmit antennas are presented and classified as frequency division multiplexing, time division multiplexing, code division multiplexing in frequencydomain, code division multiplexing in time-domain, and combinations thereof. All existing optimal training signals in the literature are special cases of the presented optimal training signals and our designs can be applied to pilot-only schemes as well as pilot-data multiplexed schemes. Index Terms—Training signal design, Pilot tone allocation,

A novel approach of blind channel estimation for OFDM systems is proposed. A linear transformation is applied on each block before it enters the OFDM system. The transform imposes a correlation structure on the transmitted blocks, which is exploited at the receiver to recover the channel via simple cross-correlation operations. The proposed approach is computationally simple and converges fast, which makes it a good candidate for estimation of fast-varying channels. Its performance is tested analytically, through a mean-square error analysis, and also via simulations. Results show that it compares favorably to the training based scheme used in the IEEE 802.11a wireless standard.

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

Abstract—We design pilot-symbol-assisted modulation for carrier frequency offset (CFO) and channel estimation in orthogonal frequency-division multiplexing transmissions over multi-input multi-output frequency-selective fading channels. The CFO and channel-estimation tasks rely on null-subcarrier and nonzero pilot symbols that we insert and hop from block to block. Because we separate CFO and channel estimation from symbol detection, the novel training patterns lead to further decoupled CFO and channel estimators. The performance of our algorithms is investigated analytically, and then compared with an existing approach by simulations. Index Terms—Carrier frequency offset (CFO), Cramér–Rao lower bound, frequency-selective channel, multi-input multioutput (MIMO)-orthogonal frequency-division multiplexing (OFDM), null subcarriers, pilot symbols. I.

We propose a novel approach for blind channel estimation over frequency selective channels in OFDM system. By introducing a non-redundant unitary precoder for each pair of blocks before they enter the OFDM system, the channel can be identified up to a complex scalar ambiguity based upon a simple cross-correlation operations applied to successive received signal blocks. It is shown that the proposed approach not only maintains the transmission power, but also provides multipath diversity and bandwidth efficiency.

Abstract — All existing training signal designs for channel estimation in OFDM systems assume no frequency offsets. In practice, frequency offset is unavoidable and seriously degrades the performance of OFDM systems. In this paper, we address the problem of designing optimal training signals for the estimation of frequency-selective channels in MIMO OFDM systems with frequency offsets. The mean square error advantage of our proposed optimal training signals can be quite significant for moderate-to-high values of SNR and frequency offsets. I.

Beyond third generation (3G) and fourth generation (4G) wireless communication systems are targeting far higher data rates, spectral efficiency and mobility requirements than existing 3G networks. By using multiple antennas at the transmitter and the receiver, multipleinput multiple-output (MIMO) technology allows improving both the spectral efficiency (bits/s/Hz), the coverage, and link reliability of the system. Multicarrier modulation such as orthogonal frequency division multiplexing (OFDM) is a powerful technique to handle impairments specific to the wireless radio channel. The combination of multicarrier modulation together with MIMO signaling provides a feasible physical layer technology for future beyond 3G and fourth generation communication systems. The theoretical benefits of MIMO and multicarrier modulation may not be fully achieved because the wireless transmission channels are time and frequency selective. Also, high data rates call for a large bandwidth and high carrier frequencies. As a result, an important Doppler spread is likely to be experienced, leading to variations of the channel over very short period of time. At the same time, transceiver front-end imperfections,

Abstract — Orthogonal frequency division multiplexing (OFDM) is a popular method for high data rate wireless transmission. OFDM may be combined with antenna arrays at the transmitter and receiver to increase the diversity gain and/or to enhance the system capacity on time-variant and frequency-selective channels, resulting in a multiple-input multiple-output (MIMO) configuration. This paper explores various physical layer research challenges in MIMO-OFDM system design, including physical channel measurements and modelling, analog beam forming techniques using adaptive antenna arrays, space-time techniques for MIMO-OFDM, error control coding techniques, OFDM preamble and packet design, and signal processing algorithms used for performing time and frequency synchronization, channel estimation, and channel tracking in MIMO-OFDM systems. Finally, the paper considers a software radio implementation of MIMO-OFDM.

Coping with time-selective fading channels is challenging, but also rewarding especially with multiantenna systems, where joint space-Doppler diversity and coding gains can be collected to enhance performance of wireless mobile links. These gains have not been quanti ed, and space-time coded systems maximizing joint space-Doppler bene ts have not been designed. Based on a parsimonious basis expansion model for the underlying time-selective (and possibly correlated) channels, we quantify these gains in closed form. Furthermore, we develop space-time-Doppler coded systems that guarantee the maximum possible space-Doppler diversity, along with the largest coding gains within all linearly coded systems. Our three novel designs exploit knowledge of the maximum Doppler spread, and each oers a uniquely desirable tradeo among: high spectral eciency, low decoding complexity, and high performance. Our analytical results are con rmed by simulations that not only validate the channel model, but also reveal the relative of merits of our three designs in comparison with an existing approach.