MIMO-UFMC Transceiver Schemes for Millimeter Wave Wireless Communications

The UFMC modulation is among the most considered solutions for the realization of beyond-OFDM air interfaces for future wireless networks. This paper focuses on the design and analysis of an UFMC transceiver equipped with multiple antennas and operating at millimeter wave carrier frequencies. The paper provides the full mathematical model of a MIMO-UFMC transceiver, taking into account the presence of hybrid analog/digital beamformers at both ends of the communication links. Then, several detection structures are proposed, both for the case of single-packet isolated transmission, and for the case of multiple-packet continuous transmission. In the latter situation, the paper also considers the case in which no guard time among adjacent packets is inserted, trading off an increased level of interference with higher values of spectral efficiency. At the analysis stage, the several considered detection structures and transmission schemes are compared in terms of bit-error-rate, root-mean-square-error, and system throughput. The numerical results show that the proposed transceiver algorithms are effective and that the linear MMSE data detector is capable of well managing the increased interference brought by the removal of guard times among consecutive packets, thus yielding throughput gains of about 10 - 13 $\%$. The effect of phase noise at the receiver is also numerically assessed, and it is shown that the recursive implementation of the linear MMSE exhibits some degree of robustness against this disturbance

Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems

In this work, decision feedback (DF) detection algorithms based on multiple processing branches for multi-input multi-output (MIMO) spatial multiplexing systems are proposed. The proposed detector employs multiple cancellation branches with receive filters that are obtained from a common matrix inverse and achieves a performance close to the maximum likelihood detector (MLD). Constrained minimum mean-squared error (MMSE) receive filters designed with constraints on the shape and magnitude of the feedback filters for the multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive implementation of the proposed MB-MMSE-DF detector is developed along with a recursive least squares-type algorithm for estimating the parameters of the receive filters when the channel is time-varying. A soft-output version of the MB-MMSE-DF detector is also proposed as a component of an iterative detection and decoding receiver structure. A computational complexity analysis shows that the MB-MMSE-DF detector does not require a significant additional complexity over the conventional MMSE-DF detector, whereas a diversity analysis discusses the diversity order achieved by the MB-MMSE-DF detector. Simulation results show that the MB-MMSE-DF detector achieves a performance superior to existing suboptimal detectors and close to the MLD, while requiring significantly lower complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications, 201

Soft-Decision-Driven Channel Estimation for Pipelined Turbo Receivers

We consider channel estimation specific to turbo equalization for multiple-input multiple-output (MIMO) wireless communication. We develop a soft-decision-driven sequential algorithm geared to the pipelined turbo equalizer architecture operating on orthogonal frequency division multiplexing (OFDM) symbols. One interesting feature of the pipelined turbo equalizer is that multiple soft-decisions become available at various processing stages. A tricky issue is that these multiple decisions from different pipeline stages have varying levels of reliability. This paper establishes an effective strategy for the channel estimator to track the target channel, while dealing with observation sets with different qualities. The resulting algorithm is basically a linear sequential estimation algorithm and, as such, is Kalman-based in nature. The main difference here, however, is that the proposed algorithm employs puncturing on observation samples to effectively deal with the inherent correlation among the multiple demapper/decoder module outputs that cannot easily be removed by the traditional innovations approach. The proposed algorithm continuously monitors the quality of the feedback decisions and incorporates it in the channel estimation process. The proposed channel estimation scheme shows clear performance advantages relative to existing channel estimation techniques.Comment: 11 pages; IEEE Transactions on Communications 201

Digital VLSI Architectures for Advanced Channel Decoders

Error-correcting codes are strongly adopted in almost every modern digital communication and storage system, such as wireless communications, optical communications, Flash memories, computer hard drives, sensor networks, and deep-space probes. New and emerging applications demand codes with better error-correcting capability. On the other hand, the design and implementation of those high-gain error-correcting codes pose many challenges. They usually involve complex mathematical computations, and mapping them directly to hardware often leads to very high complexity. This work aims to focus on Polar codes, which are a recent class of channel codes with the proven ability to reduce decoding error probability arbitrarily small as the block-length is increased, provided that the code rate is less than the capacity of the channel. This property and the recursive code-construction of this algorithms attracted wide interest from the communications community. Hardware architectures with reduced complexity can efficiently implement a polar codes decoder using either successive cancellation approximation or belief propagation algorithms. The latter offers higher throughput at high signal-to-noise ratio thanks to the inherently parallel decision-making capability of such decoder type. A new analysis on belief propagation scheduling algorithms for polar codes and on interconnection structure of the decoding trellis not covered in literature is also presented. It allowed to achieve an hardware implementation that increase the maximum information throughput under belief propagation decoding while also minimizing the implementation complexity