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.

Distributed antenna systems (DAS) have been widely implemented in state-of-the art cellular communication systems to cover dead spots. Recent academic studies have shown that in addition to coverage improvements, DAS can also have potential advantages such as reduced power and increased system capacity in a single cell environment. This paper analytically quantifies downlink capacity of multicell DAS for two different transmission strategies: selection diversity (where just one or two of the distributed antennas are used) and blanket transmission (where all antennas in the cell broadcast data). Simple repeaters are a special case of our analysis. A generalized information theoretic analysis is provided to illuminate the fundamental limits of such systems in the cellular context. The results show that DAS reduces other-cell interference in a multicell environment and hence significantly improves capacity (by about 2x), with particularly large improvements for users near cell boundaries. Less obviously, from a communication theory standpoint, it is shown that selection diversity is preferable to blanket transmission in terms of achievable ergodic capacity. For blanket transmission, we show that the optimal transmission strategy is just phase steering due to the per antenna module power constraints in DAS

Multi-antenna transmission and reception (known as MIMO) is widely touted as the key technology for enabling wireless broadband services, whose widespread success will require 10 times higher spectral efficiency than current cellular systems, at 10 times lower cost per bit. Spectrally efficient, inexpensive cellular systems are by definition densely populated and interference-limited. But spatial multiplexing MIMO systems- whose principal merit is a supposed dramatic increase in spectral efficiency- lose much of their effectiveness in high levels of interference. This article overviews several approaches to handling interference in multicell MIMO systems. The discussion is applicable to any multi-antenna cellular network, including 802.16e/WiMAX, 3GPP (HSDPA and 3GPP LTE), and 3GPP2 (lxEVDO). We argue that many of the traditional interference management techniques have limited usefulness (or are even counterproductive) when viewed in concert with MIMO. The problem of interference in MIMO systems is too large in scope to be handled with a single technique: in practice a combination of complementary countermeasures will be needed. We overview emerging system-level interference-reducing strategies based on cooperation, which will be important for overcoming interference in future spatial multiplexing cellular systems.

We investigate the effects of multi-user diversity in a spectrum sharing system where secondary users restrictively utilize a spectrum licensed to primary users only if interference perceived at primary users is regulated below a predetermined level. This interference regulation affects the characteristics of multiuser diversity gains previously known in non-spectrum sharing systems. Our numerical and analytical results show that the multiuser diversity gain in a spectrum sharing system increases differently according to conditions given by the transmit power of secondary users, P, and a predetermined interference temperature, Q - if P is sufficiently larger than Q, the multiuser diversity gain in terms of capacity scales like log₂ (W (N_s)) similarly to a previously known scaling law in the non-spectrum sharing systems, where W(middot) and N_s denote a Lambert W function and the number of secondary transmitters, respectively. However, the scaling law of multiuser diversity gain becomes log₂(N_s) as P becomes sufficiently larger such that P Gt QN_s.

Content delivery success in wireless caching helper networks depends mainly on cache-based channel selection diversity and network interference. For given channel fading and network geometry, both channel selection diversity and network interference dynamically vary according to what and how the caching helpers cache at their finite storage space. We study probabilistic content placement (or caching placement) to desirably control cache-based channel selection diversity and network interference in a stochastic wireless caching helper network, with sophisticated considerations of wireless fading channels, interactions among multiple users, such as interference and loads at caching helpers, and arbitrary memory size. Using stochastic geometry, we derive optimal caching probabilities in the closed form to maximize the average success probability of content delivery and propose an efficient algorithm to find the solution in a noise-limited network. In an interference-limited network, based on a lower bound of the average success probability of content delivery, we find near-optimal caching probabilities in the closed form to control the channel selection diversity and the network interference. We numerically verify that the proposed content placement is superior to other comparable content placement strategies.

In this paper, a novel transmission technique for the multiple-input multiple-output (MIMO) broadcast channel is proposed that allows simultaneous transmission to multiple users with limited feedback from each user. During a training phase, the base station modulates a training sequence on multiple sets of randomly chosen orthogonal beamforming vectors. Each user sends the index of the best beamforming vector and the corresponding signal-to-interference-plus-noise ratio for that set of orthogonal vectors back to the base station. The base station opportunistically determines the users and corresponding orthogonal vectors that maximize the sum capacity. Based on the capacity expressions, the optimal amount of training to maximize the sum capacity is derived as a function of the system parameters. The main advantage of the proposed system is that it provides throughput gains for the MIMO broadcast channel with a small feedback overhead, and provides these gains even with a small number of active users. Numerical simulations show that a 20% gain in sum capacity is achieved (for a small number of users) over conventional opportunistic space division multiple access, and a 100% gain (for a large number of users) over conventional opportunistic beamforming when the number of transmit antennas is four.