Angel Lozano

What Will 5G Be

What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

Five disruptive technology directions for 5G

New research directions will lead to fundamental changes in the design of future fifth generation (5G) cellular networks. This article describes five technologies that could lead to both architectural and component disruptive design changes: device-centric architectures, millimeter wave, massive MIMO, smarter devices, and native support for machine-to-machine communications. The key ideas for each technology are described, along with their potential impact on 5G and the research challenges that remain.

Impact of antenna correlation on the capacity of multiantenna channels

This paper applies random matrix theory to obtain analytical characterizations of the capacity of correlated multiantenna channels. The analysis is not restricted to the popular separable correlation model, but rather it embraces a more general representation that subsumes most of the channel models that have been treated in the literature. For arbitrary signal-to-noise ratios (SNR), the characterization is conducted in the regime of large numbers of antennas. For the low- and high-SNR regions, in turn, we uncover compact capacity expansions that are valid for arbitrary numbers of antennas and that shed insight on how antenna correlation impacts the tradeoffs among power, bandwidth, and rate.

Link-optimal space-time processing with multiple transmit and receive antennas

Previous information theory results have demonstrated the enormous capacity potential of wireless communication systems with multiple transmit and receive antennas. To exploit this potential, a number of space-time architectures have been proposed which transmit parallel data streams, simultaneously and on the same frequency, in a multiple-input multiple-output fashion. With sufficient multipath propagation, these different streams can be separated at the receiver. Mostly, these space-time schemes have been studied only in the presence of spatially white noise. We present an architecture that is optimal, in the sense of maximum link spectral efficiency, in the presence of spatially colored interference. We evaluate this new architecture and compare it, under various propagation conditions, to other adaptive-antenna techniques with equal number of antennas.

Multiple-antenna capacity in the low-power regime

This paper provides analytical characterizations of the impact on the multiple-antenna capacity of several important features that fall outside the standard multiple-antenna model, namely: (i) antenna correlation, (ii) Ricean factors, (iii) polarization diversity, and (iv) out-of-cell interference; all in the regime of low signal-to-noise ratio. The interplay of rate, bandwidth, and power is analyzed in the region of energy per bit close to its minimum value. The analysis yields practical design lessons for arbitrary number of antennas in the transmit and receive arrays.

Fundamental Limits of Cooperation

Cooperation is viewed as a key ingredient for interference management in wireless networks. This paper shows that cooperation has fundamental limitations. First, it is established that in systems that rely on pilot-assisted channel estimation, the spectral efficiency is upper-bounded by a quantity that does not depend on the transmit powers; in this framework, cooperation is possible only within clusters of limited size, which are subject to out-of-cluster interference whose power scales with that of the in-cluster signals. Second, an upper bound is also shown to exist if the cooperation extends to an entire (large) system operating as a single cluster; here, pilot-assisted transmission is necessarily transcended. Altogether, it is concluded that cooperation cannot in general change an interference-limited network to a noise-limited one. Consequently, the existing literature that routinely assumes that the high-power spectral efficiency scales with the log-scale transmit power provides only a partial characterization. The complete characterization proposed in this paper subdivides the high-power regime into a degree-of-freedom regime, where the scaling with the log-scale transmit power holds approximately, and a saturation regime, where the spectral efficiency hits a ceiling that is independent of the power. Using a cellular system as an example, it is demonstrated that the spectral efficiency saturates at power levels of operational relevance.

Layered space-time receivers for frequency-selective wireless channels

Results in information theory have demonstrated the enormous potential of wireless communication systems with antenna arrays at both the transmitter and receiver. To exploit this potential, a number of layered space-time architectures have been proposed. These layered space-time systems transmit parallel data streams, simultaneously and on the same frequency, in a multiple-input multiple-output fashion. With rich multipath propagation, these different streams can be separated at the receiver because of their distinct spatial signatures. However, the analysis of these techniques presented thus far had mostly been strictly narrowband. In order to enable high-data-rate applications, it might be necessary to utilize signals whose bandwidth exceeds the coherence bandwidth of the channel, which brings in the issue of frequency selectivity. In this paper, we present a class of layered space-time receivers devised for frequency-selective channels. These new receivers, which offer various performance and complexity tradeoffs, are compared and evaluated in the context of a typical urban channel with excellent results.

Capacity-achieving input covariance for single-user multi-antenna channels

We characterize the capacity-achieving input covariance for multi-antenna channels known instantaneously at the receiver and in distribution at the transmitter. Our characterization, valid for arbitrary numbers of antennas, encompasses both the eigenvectors and the eigenvalues. The eigenvectors are found for zero-mean channels with arbitrary fading profiles and a wide range of correlation and keyhole structures. For the eigenvalues, in turn, we present necessary and sufficient conditions as well as an iterative algorithm that exhibits remarkable properties: universal applicability, robustness and rapid convergence. In addition, we identify channel structures for which an isotropic input achieves capacity.

Approaching eigenmode BLAST channel capacity using V-BLAST with rate and power feedback

Multiple antennas at the transmitter and receiver can achieve enormous capacities by transmitting on the channels eigenmodes when the channel realization is known at the transmitter. If the transmitter has no knowledge of the channel, a significant fraction of the eigenmode capacity can be achieved in an open-loop mode, but multi-dimensional coding is required. We show how the open-loop capacity can be achieved with conventional single-dimensional coding using optimum successive decoding (OSD) and simple per-antenna rate control. Using power allocation, the capacity can be further increased, although only slightly.

Capacity of multiple-transmit multiple-receive antenna architectures

The capacity of wireless communication architectures equipped with multiple transmit and receive antennas and impaired by both noise and cochannel interference is studied. We find a closed-form solution for the capacity in the limit of a large number of antennas. This asymptotic solution, which is a sole function of the relative number of transmit and receive antennas and the signal-to-noise and signal-to-interference ratios (SNR and SIR), is then particularized to a number of cases of interest. By verifying that antenna diversity one can substitute for time and/or frequency diversity at providing ergodicity, we show that these asymptotic solutions approximate the ergodic capacity very closely even when the number of antennas is very small.