High peak-to-average power ratio of the transmit signal is a major drawback of multicarrier transmission such as OFDM or DMT. This article describes some of the important PAPR reduction techniques for multicarrier transmission including amplitude clipping and filtering, coding, partial transmit sequence, selected mapping, interleaving, tone reservation, tone injection, and active constellation extension. Also, we make some remarks on the criteria for PAPR reduction technique selection and briefly address the problem of PAPR reduction in OFDMA and MIMO-OFDM.

An overview of peak-to-average power ratio reduction techniques for multicarrier transmission

Digital Coding of Waveforms

Multiple-antenna systems, also known as multiple-input multiple-output radio, can improve the capacity and reliability of radio communication. However, the multiple RF chains associated with multiple antennas are costly in terms of size, power, and hardware. Antenna selection is a low-cost low-complexity alternative to capture many of the advantages of MIMO systems. This article reviews classic results on selection diversity, followed by a discussion of antenna selection algorithms at the transmit and receive sides. Extensions of classical results to antenna subset selection are presented. Finally, several open problems in this area are pointed out.

Antenna selection in MIMO systems

Multiple-input multiple-output (MIMO) wireless systems use antenna arrays at both the transmitter and receiver to provide communication links with substantial diversity and capacity. Spatial multiplexing is a common space-time modulation technique for MIMO communication systems where independent information streams are sent over different transmit antennas. Unfortunately, spatial multiplexing is sensitive to ill-conditioning of the channel matrix. Precoding can improve the resilience of spatial multiplexing at the expense of full channel knowledge at the transmitter-which is often not realistic. This correspondence proposes a quantized precoding system where the optimal precoder is chosen from a finite codebook known to both receiver and transmitter. The index of the optimal precoder is conveyed from the receiver to the transmitter over a low-delay feedback link. Criteria are presented for selecting the optimal precoding matrix based on the error rate and mutual information for different receiver designs. Codebook design criteria are proposed for each selection criterion by minimizing a bound on the average distortion assuming a Rayleigh-fading matrix channel. The design criteria are shown to be equivalent to packing subspaces in the Grassmann manifold using the projection two-norm and Fubini-Study distances. Simulation results show that the proposed system outperforms antenna subset selection and performs close to optimal unitary precoding with a minimal amount of feedback.

Limited feedback unitary precoding for spatial multiplexing systems

Multiple-input-multiple-output (MIMO) wireless systems are those that have multiple antenna elements at both the transmitter and receiver. They were first investigated by computer simulations in the 1980s. Since that time, interest in MIMO systems has exploded. They are now being used for third-generation cellular systems (W-CDMA) and are discussed for future high-performance modes of the highly successful IEEE 802.11 standard for wireless local area networks. MIMO-related topics also occupy a considerable part of today's academic communications research. The multiple antennas in MIMO systems can be exploited in two different ways. One is the creation of a highly effective antenna diversity system; the other is the use of the multiple antennas for the transmission of several parallel data streams to increase the capacity of the system. This article presented an overview of MIMO systems with antenna selection. The transmitter, the receiver, or both use only the signals from a subset of the available antennas. This allows considerable reductions in the hardware expense.

MIMO systems with antenna selection

Multiple antenna wireless communication systems have recently attracted significant attention due to their higher capacity and better immunity to fading as compared to systems that employ a single-sensor transceiver. Increasing the number of transmit and receive antennas enables to improve system performance at the price of higher hardware costs and computational burden. For systems with a large number of antennas, there is a strong motivation to develop techniques with reduced hardware and computational costs. An efficient approach to achieve this goal is the optimal antenna subset selection. In this paper, we propose a fast antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Our algorithm achieves almost the same outage capacity as the optimal selection technique while having lower computational complexity than the existing nearly optimal antenna selection methods. The optimality of the proposed technique is established in several important specific cases. A QR decomposition-based interpretation of our algorithm is provided that sheds a new light on the optimal antenna selection problem.

Fast antenna subset selection in MIMO systems

Orthogonal frequency-division multiplexing (OFDM) introduces large amplitude variations in time, which can result in significant signal distortion in the presence of nonlinear amplifiers. We introduce a new bound for the peak of the continuous envelope of an OFDM signal, based on the maximum of its corresponding oversampled sequence; it is shown to be very tight as the oversampling rate increases. The bound is then used to derive a closed-form probability upper bound for the complementary cumulative distribution function of the peak-to-mean envelope power ratio of uncoded OFDM signals for sufficiently large numbers of subcarriers. As another application of the bound for oversampled sequences, we propose tight relative error bounds for computation of the peak power using two main methods: the oversampled inverse fast Fourier transform and the method introduced for coded systems based on minimum distance decoding of the code.

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On the peak-to-average power of OFDM signals based on oversampling

Template matching has many applications in signal processing, image processing, pattern recognition, and video compression. This paper proposes a fast coarse-to-fine template matching algorithm for finding the exact best match, i.e., the match that may be found by a full search. This is obtained by pruning the number of candidates in the full search using the results of a coarse search. Experimental results show that speed ups of a couple of orders of magnitude can easily be achieved using this method for typical low-noise cases of two-dimensional (2-D) template matching.

A fast globally optimal algorithm for template matching using low-resolution pruning

The problem of optimal approximation of members of a vector space by a linear combination of members of a large overcomplete library of vectors is of importance in many areas including image and video coding, image analysis, control theory, and statistics. Finding the optimal solution in the general case is mathematically intractable. Matching pursuit, and its orthogonal version, provide greedy solutions to this problem. Orthogonal matching pursuit typically provides significantly better solution compared to the nonorthogonal version, but requires much more computation. This paper presents a fast algorithm for implementation of orthogonal matching pursuit which for many coding applications has a computational complexity very close to that of the nonorthogonal version.

A fast orthogonal matching pursuit algorithm

We consider the problem of joint space-time decoding and multiaccess interference (MAI) rejection in multiuser multiple-input multiple-output (MIMO) wireless communication systems. We address the case when both the receiver and multiple transmitters are equipped with multiple antennas and when space-time block codes (STBCs) are used to send the data simultaneously from each transmitter to the receiver. A new linear receiver structure is developed to decode the data sent from the transmitter-of-interest while rejecting MAI, self-interference, and noise. The proposed receivers are designed by minimizing the output power subject to constraints that zero-force self-interference and/or preserve a unity gain for all symbols of the transmitter-of-interest. Simulation results show that in multiaccess scenarios, the proposed techniques have substantially lower symbol error rates as compared with the matched filter (MF) receiver, which is equivalent to the maximum likelihood (ML) space-time decoder in the point-to-point MIMO communication case.

Mohammad Gharavi-Alkhansari

Papers

Fast antenna subset selection in MIMO systems

On the peak-to-average power of OFDM signals based on oversampling

A fast globally optimal algorithm for template matching using low-resolution pruning

A fast orthogonal matching pursuit algorithm

Minimum variance linear receivers for multiaccess MIMO wireless systems with space-time block coding