Efficient DCT-MCM Detection for Single and Multi-Antenna Wireless Systems

The discrete cosine transform (DCT) based multicarrier modulation (MCM) system is regarded as one of the promising transmission techniques for future wireless communications. By employing cosine basis as orthogonal functions for multiplexing each real-valued symbol with symbol period of T, it is able to maintain the subcarrier orthogonality while reducing frequency spacing to 1/(2T) Hz, which is only half of that compared to discrete Fourier transform (DFT) based multicarrier systems. In this paper, following one of the effective transmission models by which zeros are inserted as guard sequence and the DCT operation at the receiver is replaced by DFT of double length, we reformulate and evaluate three classic detection methods by appropriately processing the post-DFT signals both for single antenna and multiple-input multiple-output (MIMO) DCT-MCM systems. In all cases, we show that with our reformulated detection approaches, DCT-MCM schemes can outperform, in terms of error-rate, conventional OFDM-based systems

Review of Switched Beamforming Networks for Scannable Antenna Application towards Fifth Generation (5G) Technology

The next generation wireless network (5G) addresses the evolution beyond mobile internet to massive Internet-of-Things (IoT) which will take off from 2019/2020 onwards. The essential design features in 5G wireless network system are massive multiple-input and multiple-output (MIMO) and steerable antenna array. The higher capacity, lower power transmission and larger system coverage offered by upcoming 5G technology can be realized using switched-beam antenna such as Butler matrix, Rotman lens, Blass matrix and Nolen matrix. Review of their design features and performance results will be compared in this article. Butler matrix can be the best approach owing to low complexity, orthogonal beams and less components utilization

Reciprocity Calibration for Massive MIMO: Proposal, Modeling and Validation

This paper presents a mutual coupling based calibration method for time-division-duplex massive MIMO systems, which enables downlink precoding based on uplink channel estimates. The entire calibration procedure is carried out solely at the base station (BS) side by sounding all BS antenna pairs. An Expectation-Maximization (EM) algorithm is derived, which processes the measured channels in order to estimate calibration coefficients. The EM algorithm outperforms current state-of-the-art narrow-band calibration schemes in a mean squared error (MSE) and sum-rate capacity sense. Like its predecessors, the EM algorithm is general in the sense that it is not only suitable to calibrate a co-located massive MIMO BS, but also very suitable for calibrating multiple BSs in distributed MIMO systems. The proposed method is validated with experimental evidence obtained from a massive MIMO testbed. In addition, we address the estimated narrow-band calibration coefficients as a stochastic process across frequency, and study the subspace of this process based on measurement data. With the insights of this study, we propose an estimator which exploits the structure of the process in order to reduce the calibration error across frequency. A model for the calibration error is also proposed based on the asymptotic properties of the estimator, and is validated with measurement results.Comment: Submitted to IEEE Transactions on Wireless Communications, 21/Feb/201

A Digital Predistortion Scheme Exploiting Degrees-of-Freedom for Massive MIMO Systems

The primary source of nonlinear distortion in wireless transmitters is the power amplifier (PA). Conventional digital predistortion (DPD) schemes use high-order polynomials to accurately approximate and compensate for the nonlinearity of the PA. This is not practical for scaling to tens or hundreds of PAs in massive multiple-input multiple-output (MIMO) systems. There is more than one candidate precoding matrix in a massive MIMO system because of the excess degrees-of-freedom (DoFs), and each precoding matrix requires a different DPD polynomial order to compensate for the PA nonlinearity. This paper proposes a low-order DPD method achieved by exploiting massive DoFs of next-generation front ends. We propose a novel indirect learning structure which adapts the channel and PA distortion iteratively by cascading adaptive zero forcing precoding and DPD. Our solution uses a 3rd order polynomial to achieve the same performance as the conventional DPD using an 11th order polynomial for a 100x10 massive MIMO configuration. Experimental results show a 70% reduction in computational complexity, enabling ultra-low latency communications.Comment: IEEE International Conference on Communications 201

Microwave Slow-Wave Structure and Phase-Compensation Technique for Microwave Power Divider

In this paper, T-shaped electromagnetic bandgap is loaded on a coupled transmission line itself and its electric performance is studied. Results show that microwave slow-wave effect can be enhanced and therefore, size reduction of a transmission-line-based circuit is possible. However, the transmission-line-based circuits characterize varied phase responses against frequency, which becomes a disadvantage where constant phase response is required. Consequently, a phase-compensation technique is further presented and studied. For demonstration purpose, an 8-way coupled-line power divider with 22.5 degree phase shifts between adjacent output ports, based on the studied slow-wave structure and phase-compensation technique, is developed. Results show both compact circuit architecture and improved phase imbalance are realized, confirming the investigated circuit structures and analyzing methodologies