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.

Spatially Sparse Precoding in Millimeter Wave MIMO Systems

Non-orthogonal multiple access (NOMA) is an essential enabling technology for the fifth-generation (5G) wireless networks to meet the heterogeneous demands on low latency, high reliability, massive connectivity, improved fairness, and high throughput. The key idea behind NOMA is to serve multiple users in the same resource block, such as a time slot, subcarrier, or spreading code. The NOMA principle is a general framework, and several recently proposed 5G multiple access schemes can be viewed as special cases. This survey provides an overview of the latest NOMA research and innovations as well as their applications. Thereby, the papers published in this special issue are put into the context of the existing literature. Future research challenges regarding NOMA in 5G and beyond are also discussed.

A Survey on Non-Orthogonal Multiple Access for 5G Networks: Research Challenges and Future Trends

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

MIMO Broadcast Channels With Finite-Rate Feedback

It is now well known that employing channel adaptive signaling in wireless communication systems can yield large improvements in almost any performance metric. Unfortunately, many kinds of channel adaptive techniques have been deemed impractical in the past because of the problem of obtaining channel knowledge at the transmitter. The transmitter in many systems (such as those using frequency division duplexing) can not leverage techniques such as training to obtain channel state information. Over the last few years, research has repeatedly shown that allowing the receiver to send a small number of information bits about the channel conditions to the transmitter can allow near optimal channel adaptation. These practical systems, which are commonly referred to as limited or finite-rate feedback systems, supply benefits nearly identical to unrealizable perfect transmitter channel knowledge systems when they are judiciously designed. In this tutorial, we provide a broad look at the field of limited feedback wireless communications. We review work in systems using various combinations of single antenna, multiple antenna, narrowband, broadband, single-user, and multiuser technology. We also provide a synopsis of the role of limited feedback in the standardization of next generation wireless systems.

/pdf/an-overview-of-limited-feedback-in-wireless-communication-1njp2bb1kz.pdf

An overview of limited feedback in wireless communication systems

Non-orthogonal multiple access (NOMA) is an essential enabling technology for the fifth generation (5G) wireless networks to meet the heterogeneous demands on low latency, high reliability, massive connectivity, improved fairness, and high throughput. The key idea behind NOMA is to serve multiple users in the same resource block, such as a time slot, subcarrier, or spreading code. The NOMA principle is a general framework, and several recently proposed 5G multiple access schemes can be viewed as special cases. This survey provides an overview of the latest NOMA research and innovations as well as their applications. Thereby, the papers published in this special issue are put into the content of the existing literature. Future research challenges regarding NOMA in 5G and beyond are also discussed.

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

In a system with n users, the sum-rate capacity of the downlink channel grows as log log n, assuming optimal scheduling. However, optimal scheduling requires that the downlink channel state information (CSI) for all users be fully available at the base station. We show that the same capacity growth holds even if the feedback rate from the mobiles to the base station is reduced to one bit. We propose a simple scheduling method to achieve this multiuser capacity and, furthermore, we show that, by a judicious choice of the one-bit quantizer, not only the growth rate, but also most of the capacity of a fully informed system can be preserved.

Exploiting multiuser diversity with only 1-bit feedback

This work investigates the following question: subject to strictly limited (finite-rate) feedback in a multi-user multi-antenna system, what channel state information (CSI) should we send back to the transmitter, and how should it be used? Considering the class of single-beam systems, we suggest a combination of beamforming (array gain) and multi-user diversity. It has been shown that in single antenna systems, one bit of feedback per user can capture almost all gains available due to multi-user diversity, therefore we propose and analyze a compound strategy that uses one bit for multi-user diversity and any further feedback bits for beamforming. We obtain the scaling laws of this compound strategy, showing that it scales as well as any single-beam system with full transmit-CSI.

Opportunistic Beamforming with Limited Feedback

In this paper we present a simple scheme for subchannel allocation in OFDM multiuser networks in the presence of limited feedback, in particular, when only one bit of information per subchannel is available at the base station. Our objective is to maximize the sum rate capacity of the network in the downlink transmission. We show that even with very limited feedback the sum rate capacity growth is the same as the fully informed transmission. We also extend this result to the case when subchannels are correlated.

Opportunistic dynamic subchannel allocation in multiuser OFDM networks with limited feedback

In this paper, we study and compare two algorithms for transmit/receive antenna selection in MIMO channels. Generally the only way to assure optimally in antenna selection is exhaustive search, however, thus constitutes an unacceptable burden on the receiver. We describe two suboptimal algorithms in this paper. First, a separable Tx/Rx successive selection, which has excellent performance but has complexity that grows as a quadratic function of the number of antennas. Second, an algorithm that intertwines transmit and receive side selection, which has linear complexity in the number of antennas, and only a small performance penalty compared with the first algorithm, we validate the results using simulations.

http://ieeexplore.ieee.org/iel5/9626/30420/01399466.pdf

Capacity maximizing algorithms for joint transmit-receive antenna selection

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