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

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

A Survey on Mobile Edge Computing: The Communication Perspective

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.

Millimeter-Wave Cellular Wireless Networks: Potentials and Challenges

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

This article explores network densification as the key mechanism for wireless evolution over the next decade. Network densification includes densification over space (e.g, dense deployment of small cells) and frequency (utilizing larger portions of radio spectrum in diverse bands). Large-scale cost-effective spatial densification is facilitated by self-organizing networks and intercell interference management. Full benefits of network densification can be realized only if it is complemented by backhaul densification, and advanced receivers capable of interference cancellation.

Network densification: the dominant theme for wireless evolution into 5G

As the spectral efficiency of a point-to-point link in cellular networks approaches its theoretical limits, with the forecasted explosion of data traffic, there is a need for an increase in the node density to further improve network capacity. However, in already dense deployments in today's networks, cell splitting gains can be severely limited by high inter-cell interference. Moreover, high capital expenditure cost associated with high power macro nodes further limits viability of such an approach. This article discusses the need for an alternative strategy, where low power nodes are overlaid within a macro network, creating what is referred to as a heterogeneous network. We survey current state of the art in heterogeneous deployments and focus on 3GPP LTE air interface to describe future trends. A high-level overview of the 3GPP LTE air interface, network nodes, and spectrum allocation options is provided, along with the enabling mechanisms for heterogeneous deployments. Interference management techniques that are critical for LTE heterogeneous deployments are discussed in greater detail. Cell range expansion, enabled through cell biasing and adaptive resource partitioning, is seen as an effective method to balance the load among the nodes in the network and improve overall trunking efficiency. An interference cancellation receiver plays a crucial role in ensuring acquisition of weak cells and reliability of control and data reception in the presence of legacy signals.

A survey on 3GPP heterogeneous networks

Techniques for performing peer discovery to enable peer-to-peer (P2P) communication are disclosed. In an aspect, a proximity detection signal used for peer discovery may be generated based on one or more physical channels and/or signals used in a wireless network. In one design, a user equipment (UE) may generate a proximity detection signal occupying at least one resource block based on a SC-FDMA modulation technique. In another design, the UE may generate a proximity detection signal occupying at least one resource block based on an OFDMA modulation technique. The UE may generate SC-FDMA symbols or OFDMA symbols in different manners for different physical channels. In yet another design, the UE may generate a proximity detection signal including a primary synchronization signal and a secondary synchronization signal. For all designs, the UE may transmit the proximity detection signal to indicate its presence and to enable other UEs to detect the UE.

Transmission and reception of proximity detection signal for peer discovery

Techniques for efficiently assigning resources for spurts of traffic in a wireless communication system are described. The system may support semi-persistent and non-persistent resource assignments. A semi-persistent resource assignment is valid for as long as more data is sent within a predetermined time period of last sent data and expires if no data is sent within the predetermined time period. A non-persistent resource assignment is valid for a predetermined duration or a specific transmission. A semi-persistent resource assignment may be granted for an expected spurt of data to send via the communication link. For Voice-over-Internet Protocol (VoIP), a semi-persistent resource assignment may be granted for a voice frame in anticipation of a spurt of voice activity, and a non-persistent resource assignment may be granted for a silence descriptor (SID) frame during a period of silence.

Semi-persistent scheduling for traffic spurts in wireless communication

Long term evolution (LTE)/LTE- Advanced (LTE-A) deployments with unlicensed spectrum leverage more efficient LTE communication aspects over unlicensed spectrum, such as over WIFI radio access technology. In order to accommodate such communications, various downlink procedures may be modified in order to handle communications between licensed and unlicensed spectrum with LTE/LTE-A deployments with unlicensed spectrum.

Downlink procedures for lte/lte-a communication systems with unlicensed spectrum

Aspects disclosed herein relate to channel and interference estimations in a coordinated multi-point (CoMP) environment. In the disclosed aspects, an eNB may be equipped to signal an identifier indicating a plurality of resource patterns, each associated with a resource pattern group, and each including a first resource element pattern for channel estimation and a second resource element pattern for interference estimation. The UE may be equipped to receive the signaling and perform channel estimation based at least in part on the first resource element pattern, and interference estimation based at least in part on the second resource pattern generate at least one channel state report based on the channel and interference estimations, and transmit at least one channel state report to an eNB. The eNB may determine one or more resources for use by the UE based on the at least one received channel state report.

Tao Luo

Papers

A survey on 3GPP heterogeneous networks

Transmission and reception of proximity detection signal for peer discovery

Semi-persistent scheduling for traffic spurts in wireless communication

Downlink procedures for lte/lte-a communication systems with unlicensed spectrum

Method and apparatus for enabling channel and interference estimations in macro/rrh system