MIMO techniques in WiMAX and LTE: a feature overview
TL;DR: A survey of the MIMO techniques in the two standards, IEEE 802.16e/m and 3GPP LTE/LTE-Advanced, which compares the features of the two and depicts the engineering considerations.
Abstract: IEEE 802.16m and 3GPP LTE-Advanced are the two evolving standards targeting 4G wireless systems. In both standards, multiple-input multiple-output antenna technologies play an essential role in meeting the 4G requirements. The application of MIMO technologies is one of the most crucial distinctions between 3G and 4G. It not only enhances the conventional point-to-point link, but also enables new types of links such as downlink multiuser MIMO. A large family of MIMO techniques has been developed for various links and with various amounts of available channel state information in both IEEE 802.16e/m and 3GPP LTE/LTE-Advanced. In this article we provide a survey of the MIMO techniques in the two standards. The MIMO features of the two are compared, and the engineering considerations are depicted.
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TL;DR: This article provides an overview of signal processing challenges in mmWave wireless systems, with an emphasis on those faced by using MIMO communication at higher carrier frequencies.
Abstract: Communication at millimeter wave (mmWave) frequencies is defining a new era of wireless communication. The mmWave band offers higher bandwidth communication channels versus those presently used in commercial wireless systems. The applications of mmWave are immense: wireless local and personal area networks in the unlicensed band, 5G cellular systems, not to mention vehicular area networks, ad hoc networks, and wearables. Signal processing is critical for enabling the next generation of mmWave communication. Due to the use of large antenna arrays at the transmitter and receiver, combined with radio frequency and mixed signal power constraints, new multiple-input multiple-output (MIMO) communication signal processing techniques are needed. Because of the wide bandwidths, low complexity transceiver algorithms become important. There are opportunities to exploit techniques like compressed sensing for channel estimation and beamforming. This article provides an overview of signal processing challenges in mmWave wireless systems, with an emphasis on those faced by using MIMO communication at higher carrier frequencies.
2,380 citations
Additional excerpts
...For random multipath variations, M, Mt and Mr can be defined by replacing |[Hb]`,m|2 with E|[Hb]`,m|2....
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TL;DR: A comprehensive survey of mmWave communications for future mobile networks (5G and beyond) is presented, including an overview of the solution for multiple access and backhauling, followed by the analysis of coverage and connectivity.
Abstract: Millimeter wave (mmWave) communications have recently attracted large research interest, since the huge available bandwidth can potentially lead to the rates of multiple gigabit per second per user Though mmWave can be readily used in stationary scenarios, such as indoor hotspots or backhaul, it is challenging to use mmWave in mobile networks, where the transmitting/receiving nodes may be moving, channels may have a complicated structure, and the coordination among multiple nodes is difficult To fully exploit the high potential rates of mmWave in mobile networks, lots of technical problems must be addressed This paper presents a comprehensive survey of mmWave communications for future mobile networks (5G and beyond) We first summarize the recent channel measurement campaigns and modeling results Then, we discuss in detail recent progresses in multiple input multiple output transceiver design for mmWave communications After that, we provide an overview of the solution for multiple access and backhauling, followed by the analysis of coverage and connectivity Finally, the progresses in the standardization and deployment of mmWave for mobile networks are discussed
887 citations
TL;DR: This tutorial explores the fundamental issues involved in selecting the best communications approaches for mmWave frequencies, and provides insights, challenges, and appropriate uses of each MIMO technique based on early knowledge of the mmWave propagation environment.
Abstract: The use of mmWave frequencies for wireless communications offers channel bandwidths far greater than previously available, while enabling dozens or even hundreds of antenna elements to be used at the user equipment, base stations, and access points. To date, MIMO techniques, such as spatial multiplexing, beamforming, and diversity, have been widely deployed in lower-frequency systems such as IEEE 802.11n/ac (wireless local area networks) and 3GPP LTE 4G cellphone standards. Given the tiny wavelengths associated with mmWave, coupled with differences in the propagation and antennas used, it is unclear how well spatial multiplexing with multiple streams will be suited to future mmWave mobile communications. This tutorial explores the fundamental issues involved in selecting the best communications approaches for mmWave frequencies, and provides insights, challenges, and appropriate uses of each MIMO technique based on early knowledge of the mmWave propagation environment.
613 citations
Additional excerpts
...16e/m, 4G cellular LTE, and LTEAdvanced (LTE-A) [1, 6]....
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...Both open-loop and closed-loop SM are supported in wide area network standards such as IEEE 802.16e/m, 4G cellular LTE, and LTEAdvanced (LTE-A) [1, 6]....
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TL;DR: A general survey of the SM design framework as well as of its intrinsic limits is provided, focusing on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/cooperative protocol design issues, and on their meritorious variants.
Abstract: A new class of low-complexity, yet energy-efficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely, the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO), has emerged. These systems are capable of exploiting the spatial dimensions (i.e., the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication while relying on a single-Radio Frequency (RF) chain. Moreover, SM may be also viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/cooperative protocol design issues, and on their meritorious variants.
558 citations
Additional excerpts
...Hence they have been adopted in most of the recent communication standards, such as IEEE 802.11n, IEEE 802.16e, and 3GPP Long-Term Evolution (LTE) [5], [6]....
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...[5] Q. Li et al., “MIMO techniques in WiMAX and LTE: A feature overview,” IEEE Commun....
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...[151] L. Hanzo, J. Akhtman, L. Wang, and M. Jiang, MIMO-OFDM for LTE, WiFi and WiMAX: Coherent Versus Non-Coherent and Cooperative Turbo Transceivers....
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...[137] N. B. Mehta, A. F. Molisch, and S. Kashyap, “Antenna selection in LTE: From motivation to specification,” IEEE Commun....
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...[6] F. Boccardi et al., “Multiple-antenna techniques in LTE-advanced,” IEEE Commun....
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TL;DR: The preliminary outcomes of extensive research on mmWave massive MIMO are presented and emerging trends together with their respective benefits, challenges, and proposed solutions are highlighted to point out current trends, evolving research issues and future directions on this technology.
Abstract: Several enabling technologies are being explored for the fifth-generation (5G) mobile system era. The aim is to evolve a cellular network that remarkably pushes forward the limits of legacy mobile systems across all dimensions of performance metrics. One dominant technology that consistently features in the list of the 5G enablers is the millimeter-wave (mmWave) massive multiple-input-multiple-output (massive MIMO) system. It shows potentials to significantly raise user throughput, enhance spectral and energy efficiencies and increase the capacity of mobile networks using the joint capabilities of the huge available bandwidth in the mmWave frequency bands and high multiplexing gains achievable with massive antenna arrays. In this survey, we present the preliminary outcomes of extensive research on mmWave massive MIMO (as research on this subject is still in the exploratory phase) and highlight emerging trends together with their respective benefits, challenges, and proposed solutions. The survey spans broad areas in the field of wireless communications, and the objective is to point out current trends, evolving research issues and future directions on mmWave massive MIMO as a technology that will open up new frontiers of services and applications for next-generation cellular networks.
491 citations
Cites background from "MIMO techniques in WiMAX and LTE: a..."
...It employs an antenna array system with a few hundred BS antennas simultaneously serving many tens of user terminals in the same time-frequency resource [21], [32]....
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...3) Multi-User MIMO [N > 1, M > 1, Mk = 1 and K > 1] MIMO systems have two basic configurations: SUMIMO and MU-MIMO [29], [32]....
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...However, MU-MIMO exploits multi-user diversity in the spatial domain by allocating a time-frequency resource to multiple users, which results in significant gains over SU-MIMO, particularly when the channels are spatially correlated [32]....
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...following [17], [18], [21], [32]: • Need for simple, linear and real-time techniques and hardware for optimized processing of the vast amounts of generated baseband data, at associated internal power consumption....
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References
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AT&T1
TL;DR: This paper presents a simple two-branch transmit diversity scheme that provides the same diversity order as maximal-ratio receiver combining (MRRC) with one transmit antenna, and two receive antennas.
Abstract: This paper presents a simple two-branch transmit diversity scheme. Using two transmit antennas and one receive antenna the scheme provides the same diversity order as maximal-ratio receiver combining (MRRC) with one transmit antenna, and two receive antennas. It is also shown that the scheme may easily be generalized to two transmit antennas and M receive antennas to provide a diversity order of 2M. The new scheme does not require any bandwidth expansion or any feedback from the receiver to the transmitter and its computation complexity is similar to MRRC.
13,706 citations
"MIMO techniques in WiMAX and LTE: a..." refers methods in this paper
...For a configuration with two transmit antennas, both standards have adopted the frequency domain version of the Alamouti code [ 10 ] as the basic transmit diversity MIMO mode, where pairs of adjacent subcarriers are coded together instead of two adjacent time slots....
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TL;DR: In this article, the authors examined the performance of using multi-element array (MEA) technology to improve the bit-rate of digital wireless communications and showed that with high probability extraordinary capacity is available.
Abstract: This paper is motivated by the need for fundamental understanding of ultimate limits of bandwidth efficient delivery of higher bit-rates in digital wireless communications and to also begin to look into how these limits might be approached. We examine exploitation of multi-element array (MEA) technology, that is processing the spatial dimension (not just the time dimension) to improve wireless capacities in certain applications. Specifically, we present some basic information theory results that promise great advantages of using MEAs in wireless LANs and building to building wireless communication links. We explore the important case when the channel characteristic is not available at the transmitter but the receiver knows (tracks) the characteristic which is subject to Rayleigh fading. Fixing the overall transmitted power, we express the capacity offered by MEA technology and we see how the capacity scales with increasing SNR for a large but practical number, n, of antenna elements at both transmitter and receiver.
We investigate the case of independent Rayleigh faded paths between antenna elements and find that with high probability extraordinary capacity is available. Compared to the baseline n = 1 case, which by Shannon‘s classical formula scales as one more bit/cycle for every 3 dB of signal-to-noise ratio (SNR) increase, remarkably with MEAs, the scaling is almost like n more bits/cycle for each 3 dB increase in SNR. To illustrate how great this capacity is, even for small n, take the cases n = 2, 4 and 16 at an average received SNR of 21 dB. For over 99% of the channels the capacity is about 7, 19 and 88 bits/cycle respectively, while if n = 1 there is only about 1.2 bit/cycle at the 99% level. For say a symbol rate equal to the channel bandwith, since it is the bits/symbol/dimension that is relevant for signal constellations, these higher capacities are not unreasonable. The 19 bits/cycle for n = 4 amounts to 4.75 bits/symbol/dimension while 88 bits/cycle for n = 16 amounts to 5.5 bits/symbol/dimension. Standard approaches such as selection and optimum combining are seen to be deficient when compared to what will ultimately be possible. New codecs need to be invented to realize a hefty portion of the great capacity promised.
10,526 citations
TL;DR: A simple encoding algorithm is introduced that achieves near-capacity at sum rates of tens of bits/channel use and regularization is introduced to improve the condition of the inverse and maximize the signal-to-interference-plus-noise ratio at the receivers.
Abstract: Recent theoretical results describing the sum capacity when using multiple antennas to communicate with multiple users in a known rich scattering environment have not yet been followed with practical transmission schemes that achieve this capacity. We introduce a simple encoding algorithm that achieves near-capacity at sum rates of tens of bits/channel use. The algorithm is a variation on channel inversion that regularizes the inverse and uses a "sphere encoder" to perturb the data to reduce the power of the transmitted signal. This work is comprised of two parts. In this first part, we show that while the sum capacity grows linearly with the minimum of the number of antennas and users, the sum rate of channel inversion does not. This poor performance is due to the large spread in the singular values of the channel matrix. We introduce regularization to improve the condition of the inverse and maximize the signal-to-interference-plus-noise ratio at the receivers. Regularization enables linear growth and works especially well at low signal-to-noise ratios (SNRs), but as we show in the second part, an additional step is needed to achieve near-capacity performance at all SNRs.
1,796 citations
"MIMO techniques in WiMAX and LTE: a..." refers methods in this paper
...Zero-forcing MU-MIMO [ 9 ] is one linear MU-MIMO technique commonly assumed in both standards, where the precoding matrix at the transmitter is not unitary....
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TL;DR: A key finding is that the feedback rate per mobile must be increased linearly with the signal-to-noise ratio (SNR) (in decibels) in order to achieve the full multiplexing gain.
Abstract: Multiple transmit antennas in a downlink channel can provide tremendous capacity (i.e., multiplexing) gains, even when receivers have only single antennas. However, receiver and transmitter channel state information is generally required. In this correspondence, a system where each receiver has perfect channel knowledge, but the transmitter only receives quantized information regarding the channel instantiation is analyzed. The well-known zero-forcing transmission technique is considered, and simple expressions for the throughput degradation due to finite-rate feedback are derived. A key finding is that the feedback rate per mobile must be increased linearly with the signal-to-noise ratio (SNR) (in decibels) in order to achieve the full multiplexing gain. This is in sharp contrast to point-to-point multiple-input multiple-output (MIMO) systems, in which it is not necessary to increase the feedback rate as a function of the SNR
1,717 citations
TL;DR: A novel algorithm is developed that is inspired by the Pohst enumeration strategy and is shown to offer a significant reduction in complexity compared to the Viterbo-Boutros sphere decoder and is supported by intuitive arguments and simulation results in many relevant scenarios.
Abstract: Maximum-likelihood (ML) decoding algorithms for Gaussian multiple-input multiple-output (MIMO) linear channels are considered. Linearity over the field of real numbers facilitates the design of ML decoders using number-theoretic tools for searching the closest lattice point. These decoders are collectively referred to as sphere decoders in the literature. In this paper, a fresh look at this class of decoding algorithms is taken. In particular, two novel algorithms are developed. The first algorithm is inspired by the Pohst enumeration strategy and is shown to offer a significant reduction in complexity compared to the Viterbo-Boutros sphere decoder. The connection between the proposed algorithm and the stack sequential decoding algorithm is then established. This connection is utilized to construct the second algorithm which can also be viewed as an application of the Schnorr-Euchner strategy to ML decoding. Aided with a detailed study of preprocessing algorithms, a variant of the second algorithm is developed and shown to offer significant reductions in the computational complexity compared to all previously proposed sphere decoders with a near-ML detection performance. This claim is supported by intuitive arguments and simulation results in many relevant scenarios.
1,410 citations