Millimeter wave (mmWave) communications has been regarded as a key enabling technology for 5G networks, as it offers orders of magnitude greater spectrum than current cellular bands. In contrast to conventional multiple-input–multiple-output (MIMO) systems, precoding in mmWave MIMO cannot be performed entirely at baseband using digital precoders, as only a limited number of signal mixers and analog-to-digital converters can be supported considering their cost and power consumption. As a cost-effective alternative, a hybrid precoding transceiver architecture, combining a digital precoder and an analog precoder, has recently received considerable attention. However, the optimal design of such hybrid precoders has not been fully understood. In this paper, treating the hybrid precoder design as a matrix factorization problem, effective alternating minimization (AltMin) algorithms will be proposed for two different hybrid precoding structures, i.e., the fully-connected and partially-connected structures. In particular, for the fully-connected structure, an AltMin algorithm based on manifold optimization is proposed to approach the performance of the fully digital precoder, which, however, has a high complexity. Thus, a low-complexity AltMin algorithm is then proposed, by enforcing an orthogonal constraint on the digital precoder. Furthermore, for the partially-connected structure, an AltMin algorithm is also developed with the help of semidefinite relaxation. For practical implementation, the proposed AltMin algorithms are further extended to the broadband setting with orthogonal frequency division multiplexing modulation. Simulation results will demonstrate significant performance gains of the proposed AltMin algorithms over existing hybrid precoding algorithms. Moreover, based on the proposed algorithms, simulation comparisons between the two hybrid precoding structures will provide valuable design insights.
With the formidable growth of various booming wireless communication services that require ever increasing data throughputs, the conventional microwave band below 10 GHz, which is currently used by almost all mobile communication systems, is going to reach its saturation point within just a few years. Therefore, the attention of radio system designers has been pushed toward ever higher segments of the frequency spectrum in a quest for increased capacity. In this article we investigate the feasibility, advantages, and challenges of future wireless communications over the Eband frequencies. We start with a brief review of the history of the E-band spectrum and its light licensing policy as well as benefits challenges. Then we introduce the propagation characteristics of E-band signals, based on which some potential fixed and mobile applications at the E-band are investigated. In particular, we analyze the achievability of a nontrivial multiplexing gain in fixed point-to-point E-band links, and propose an E-band mobile broadband (EMB) system as a candidate for the next generation mobile communication networks. The channelization and frame structure of the EMB system are discussed in detail. 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. Millimeter-wave (mmW) frequencies between 30 and 300 GHz are a new frontier for cellular communication that offers the promise of orders of magnitude greater bandwidths combined with further gains via beamforming and spatial multiplexing from multielement antenna arrays. This paper surveys measurements and capacity studies to assess this technology with a focus on small cell deployments in urban environments. The conclusions are extremely encouraging; measurements in New York City at 28 and 73 GHz demonstrate that, even in an urban canyon environment, significant non-line-of-sight (NLOS) outdoor, street-level coverage is possible up to approximately 200 m from a potential low-power microcell or picocell base station. In addition, based on statistical channel models from these measurements, it is shown that mmW systems can offer more than an order of magnitude increase in capacity over current state-of-the-art 4G cellular networks at current cell densities. Cellular systems, however, will need to be significantly redesigned to fully achieve these gains. Specifically, the requirement of highly directional and adaptive transmissions, directional isolation between links, and significant possibilities of outage have strong implications on multiple access, channel structure, synchronization, and receiver design. To address these challenges, the paper discusses how various technologies including adaptive beamforming, multihop relaying, heterogeneous network architectures, and carrier aggregation can be leveraged in the mmW context. Due to the high cost and power consumption of radio frequency (RF) chains, millimeter wave (mm-wave) communica- tion systems equipped with large antenna arrays typically employ less RF chains than the antenna elements. This leads to the use of a hybrid MIMO processor consisting of a RF beamformer and a baseband MIMO processor in mm-wave communications. In this paper, we consider amplify-and-forward (AF) relay-assisted mm- wave systems with the hybrid MIMO processors over frequency- selective channels. We develop an iterative algorithm for jointly designing the receive transmit (Rx Tx) RF baseband processors of the relay based on the orthogonal matching pursuit (OMP) algorithm for sparse approximation, while assuming orthogonal frequency division multiplexing (OFDM) signaling. Simulation results show that the proposed method outperforms the conven- tional method that designs the baseband processor after steering the RF beams. The ever growing traffic explosion in mobile communications has recently drawn increased attention to the large amount of underutilized spectrum in the millimeter-wave frequency bands as a potentially viable solution for achieving tens to hundreds of times more capacity compared to current 4G cellular networks. Historically, mmWave bands were ruled out for cellular usage mainly due to concerns regarding short-range and non-line-of-sight coverage issues. In this article, we present recent results from channel measurement campaigns and the development of advanced algorithms and a prototype, which clearly demonstrate that the mmWave band may indeed be a worthy candidate for next generation (5G) cellular systems. The results of channel measurements carried out in both the United States and Korea are summarized along with the actual free space propagation measurements in an anechoic chamber. Then a novel hybrid beamforming scheme and its link- and system-level simulation results are presented. Finally, recent results from our mmWave prototyping efforts along with indoor and outdoor test results are described to assert the feasibility of mmWave bands for cellular usage. We consider the design of a hybrid multiple-input multiple-output (MIMO) processor consisting of a radio frequency (RF) beamformer and a baseband MIMO processor for millimeter-wave communications over multiuser interference channels. Sparse approximation problems are formulated to design hybrid MIMO processors approximating the minimum-mean-square-error transmit receive processors in MIMO interference channels. They are solved by orthogonal-matching-pursuit-based algorithms that successively select RF beamforming vectors from a set of candidate vectors and optimize the corresponding baseband processor in the least squares sense. It is shown that various beamformers can be designed by considering different types of candidate vector sets. Simulation results demonstrate the advantage of the proposed design over the conventional method that designs the baseband processor after steering the RF beams. Massive multiple-input multiple-output (MIMO) is envisioned to offer considerable capacity improvement, but at the cost of high complexity of the hardware. In this paper, we propose a low-complexity hybrid precoding scheme to approach the performance of the traditional baseband zero-forcing (ZF) precoding (referred to as full-complexity ZF), which is considered a virtually optimal linear precoding scheme in massive MIMO systems. The proposed hybrid precoding scheme, named phased-ZF (PZF), essentially applies phase-only control at the RF domain and then performs a low-dimensional baseband ZF precoding based on the effective channel seen from baseband. Heavily quantized RF phase control up to 2 bits of precision is also considered and shown to incur very limited degradation. The proposed scheme is simulated in both ideal Rayleigh fading channels and sparsely scattered millimeter wave (mmWave) channels, both achieving highly desirable performance. Millimeter wave (mmWave) multiple-input multipleoutput (MIMO) communication with large antenna arrays has been proposed to enable gigabit per second communication for next generation cellular systems and local area networks. A key difference relative to lower frequency solutions is that in mmWave systems, precoding combining can not be performed entirely at digital baseband, due to the high cost and power consumption of some components of the radio frequency (RF) chain. In this paper we develop a low complexity algorithm for finding hybrid precoders that split the precoding combining process between the analog and digital domains. Our approach exploits sparsity in the received signal to formulate the design of the precoder combiners as a compressed sensing optimization problem. We use the properties of the matrix containing the array response vectors to find first an orthonormal analog precoder, since sparse approximation algorithms applied to orthonormal sensing matrices are based on simple computations of correlations. Then, we propose to perform a local search to refine the analog precoder and compute the baseband precoder. We present numerical results demonstrate substantial improvements in complexity while maintaining good spectral efficiency. Millimeter-wave wireless systems are emerging as a promising technology for meeting the exploding capacity requirements of wireless communication networks. Besides large bandwidths, small wavelengths at mm-wave lead to a high-dimensional spatial signal space, that can be exploited for significant capacity gains through high-dimensional multiple-input multiple-output (MIMO) techniques. In conventional MIMO approaches, optimal performance requires prohibitively high transceiver complexity. By combining the concept of beamspace MIMO communication with a hybrid analog-digital transceiver, continuous aperture phased (CAP) MIMO achieves near-optimal performance with dramatically lower complexity. This paper presents a framework for physically-accurate computational modeling and analysis of CAP-MIMO, and reports measurement results on a DLA-based prototype for multimode line-of-sight communication. The model, based on a critically sampled system representation, is used to demonstrate the performance gains of CAP-MIMO over state-of-the-art designs at mm-wave. For example, a CAP-MIMO system can achieve a spectral efficiency of 10-20 bits s Hz with a 17-31 dB power advantage over state-of-the-art, corresponding to a data rate of 10-200 Gbps with 1-10 GHz system bandwidth. The model is refined to analyze critical sources of power loss in an actual multimode system. The prototype-based measurement results closely follow the theoretical predictions, validating CAP-MIMO theory, and illustrating the utility of the model.  In order to support high-data-rate wireless communication links, millimeter wave (mmWave) systems need to overcome considerable propagation attenuation. In mmWave systems, the small wavelength enables pre-processing exploiting large antenna arrays to provide the required gain. Generally, in traditional microwave systems, pre-processing is done at the digital baseband. However, the cost and power consumption of a radio frequency (RF) chain, which carries out translation between RF and digital baseband, is too high. It is impossible to afford one for each antenna element. This hardware limitation places additional constraints on pre-processing design. In this paper, we use hybrid spatial processing architecture with a lower number of RF chains than the antenna elements. We propose a joint design of digital baseband pre-processing and post-processing based on a weighted minimum mean-squared error (MMSE) criterion subject to the transmit power constraint. Then, the optimization in the RF domain is specified into three criteria according to various error weights. For ease of hardware implementation, we develop a lower complexity transceiver in which pre-processing in RF domain after upconversion is implemented merely using analog phase shifters. Finally, we evaluate our proposed scheme by means of simulation. Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates thanks to the large bandwidth available at mmWave frequencies. To realize sufficient link margin, mmWave systems will employ directional beamforming with large antenna arrays at both the transmitter and receiver. Due to the high cost and power consumption of gigasample mixed-signal devices, mmWave precoding will likely be divided among the analog and digital domains. The large number of antennas and the presence of analog beamforming requires the development of mmWave-specific channel estimation and precoding algorithms. This paper develops an adaptive algorithm to estimate the mmWave channel parameters that exploits the poor scattering nature of the channel. To enable the efficient operation of this algorithm, a novel hierarchical multi-resolution codebook is designed to construct training beamforming vectors with different beamwidths. For single-path channels, an upper bound on the estimation error probability using the proposed algorithm is derived, and some insights into the efficient allocation of the training power among the adaptive stages of the algorithm are obtained. The adaptive channel estimation algorithm is then extended to the multi-path case relying on the sparse nature of the channel. Using the estimated channel, this paper proposes a new hybrid analog digital precoding algorithm that overcomes the hardware constraints on the analog-only beamforming, and approaches the performance of digital solutions. Simulation results show that the proposed low-complexity channel estimation algorithm achieves comparable precoding gains compared to exhaustive channel training algorithms. The results illustrate that the proposed channel estimation and precoding algorithms can approach the coverage probability achieved by perfect channel knowledge even in the presence of interference. A millimeter wave (mm-wave) communication system provides multi-Gb s data rates in short-distance transmission. Because millimeter waves have short wavelength, transceivers can be composed of large antenna arrays to alleviate severe signal attenuation. Furthermore, the link performance can be improved by adopting precoding technology in multiple data stream transmission. However, the complexity of radio frequency (RF) chains increases when large antenna arrays are used in mm-wave systems. To reduce the hardware cost, the precoding circuit can be jointly designed in both analog and digital domains to reduce the required number of RF chains. This paper proposes a new method of building the joint RF and baseband precoder that reduces the computation complexity of the original precoder reconstruction algorithm and enables highly parallel hardware architecture. Moreover, the proposed precoder reconstruction algorithm was designed and implemented using TSMC 90-nm UTM CMOS technology. The proposed precoder reconstruction processor supports the transmissions of one to four data streams for 8 × 8 mm-wave multiple-input multiple-output systems. The operating frequency of this chip was 167 MHz, and the power consumption was 243.2 mW when the supply voltage was 1 V. The core area of the postlayout result was about 3.94 mm 2 . The proposed processor achieved 4, 4.9, 6.7, and 6.7 M channel matrices per second in four-, three-, two-, and one-stream modes, respectively. Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications and all cellular systems. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered.