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

A selection process is disclosed for a user equipment (UE) to select between a WAN and a WLAN. Instead of defaulting to select one or the other networks, as long as the connection is available, a better load balancing and maximization of the system capacity may be achieved when the UE selects the network according to a priority order between the WAN/WLAN. The priority order takes into account various network metrics, such as loading, channel conditions, bandwidth, and service requirements.

WAN-WLAN cell selection in UEs

Devices and methods are provided for transmit power control in a wireless communication environment. In one embodiment, the method may involve measuring an interference amount over at least one of a sub-band and a full bandwidth. The method may involve assigning a level to the measured interference amount, the level comprising one of an overloaded level and an underloaded level. The method may involve encoding the level as an overload indicator, the overload indicator being conditioned on the sub-band such that the overload indicator includes enhanced layer symbols regarding the level of the measured interference amount. The method may involve conveying the overload indicator to at least one mobile device.

System and method for overload indication

Methods, systems, and devices are described for increased wireless communications system capacity through hierarchical modulation of multiple transmission layers during certain transmission subframes in a wireless communications system. Various deployment scenarios may be supported that may provide communications modulated on both a base modulation layer as well as on an enhancement modulation layer that is superpositioned on the base modulation layer. Reference signals may be provided for channel estimation for both the base modulation layer and enhancement modulation layer.

Overlay unicast or mbsfn data transmission on top of mbsfn transmission

A method by a small cell for wireless communication may include receiving, by the small cell, a wireless Multicast-Broadcast Single Frequency Network (MBSFN) signal from a macro cell, wherein the small cell is characterized by having a transmit power substantially less than each macro cell in a wireless communication network with the small cell. The method may further include obtaining, by the small cell, a measurement value of the MBSFN signal within a radio range of the small cell. The method may further include acting, by the small cell, based on the measurement value. The small cell may be, or may include, at least one of a pico cell, a femto cell, or a home evolved Node B (HeNB).

Small cell evolved multimedia broadcast multicast service

An example data structure for managing user equipment communications in a wireless communications system is presented, as well as methods and apparatuses configured to implement the data structure. For instance, the data structure may include a downlink subframe comprising two slots and including one or more quick downlink channels having a single-slot transmission time interval. In addition, the example data structure may include one or more resource element blocks each comprising one or more resource elements into which a frequency bandwidth is divided within one or both of the two slots, wherein each of the one or more resource element blocks comprises a control channel region or a data channel region. Furthermore, the example data structure may include one or more resource grants, located within one or more control channel regions, for one or more user equipment served by the one or more quick downlink channels.

Yongbin Wei

Papers

WAN-WLAN cell selection in UEs

System and method for overload indication

Overlay unicast or mbsfn data transmission on top of mbsfn transmission

Small cell evolved multimedia broadcast multicast service

Downlink channel design for lte with low latency