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

Techniques are described for wireless communication. One method includes monitoring, by a first base station of a first operator, for clear channel assessment (CCA) exempt transmission (CET) timing information of a second base station of a second operator; identifying transmission timings of CETs of the second base station of the second operator based at least in part on the monitoring; and discontinuing transmissions of the first base station of the first operator during the transmission timings of the CETs of the second base station of the second operator. Transmissions of the second base station of the second operator may be asynchronous to transmissions of the first base station of the first operator.

Techniques for enabling asynchronous transmissions in an unlicensed radio frequency spectrum band

Detection and reporting techniques for collisions between transmitters of two different radio access technologies (RATs) transmitting in a shared radio frequency spectrum band is described. The collision may occur following a listen-before-talk procedure but prior to transmission of data, and may not affect the reception of the transmitted data. Collisions may be detected using for example, energy sensing, preamble or ready-to-send (RTS) signal detection, or unsuccessful decoding of all or part of a channel reservation signal. A transmitting device may determine a collision has occurred by detecting an energy level during a preamble transmission is greater than a threshold level or by detecting that an energy level during a transmission gap of a time-domain energy pattern is above a threshold level. A receiving device, such as a user equipment (UE), that detects the collision may report the collision to the transmitter.

Collision detection in a shared radio frequency spectrum band

Methods and apparatuses are described in which an unlicensed spectrum is used for Long Term Evolution (LTE) communications. A first method includes broadcasting beacon signals in an unlicensed spectrum at predetermined times from an evolved Node B (eNB). A second method includes receiving beacon signals broadcast in an unlicensed spectrum at predetermined times from an eNB. The beacon signals may include downlink signals identifying the eNB and at least one associated attribute of the eNB.

Beacon transmission over unlicensed spectrum

Methods and apparatus are provided for assigning interference measurement resources. A method includes receiving at least one identifier, which determines, at least in part, at least one interference measurement resource that partially overlaps with another at least one interference measurement resource. The at least one interference measurement resource comprises a number of resource elements out of a set of resource elements. The method also includes measuring interference based at least in part on the at least one interference measurement resource.

Randomization procedure for assigning interference measurement resources in wireless communication

Techniques are described for wireless communication. One method includes monitoring, by a first base station of a first operator, for uplink configuration information and downlink configuration information associated with a second base station of at least one second operator; identifying a transmission timing of one or more uplink transmissions to the second base station of the at least one second operator based at least in part on the uplink configuration information; and prohibiting access to an unlicensed radio frequency spectrum band by the first base station of the first operator during the identified transmission timing of the one or more uplink transmissions. Transmissions of the second base station of the at least one second operator in the unlicensed radio frequency spectrum band may be asynchronous to transmissions of the first base station of the first operator in the unlicensed radio frequency spectrum band.

Yongbin Wei

Papers

Techniques for enabling asynchronous transmissions in an unlicensed radio frequency spectrum band

Collision detection in a shared radio frequency spectrum band

Beacon transmission over unlicensed spectrum

Randomization procedure for assigning interference measurement resources in wireless communication

Techniques for enabling asynchronous time division duplexing transmissions in an unlicensed radio frequency spectrum band