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

The broad connection of devices to the Internet, known as the IoT or M2M, requires lowcost power-efficient global connectivity services. New physical layer solutions, MAC procedures, and network architectures are needed to evolve the current LTE cellular systems to meet the demands of IoT services. Several steps have been taken under the 3GPP to accomplish these objectives and are included in the upcoming 3GPP LTE standards release (3GPP Release 13). In this tutorial article, we present an overview of several features included in 3GPP to accommodate the needs of M2M communications, including changes in the physical layer such as enhanced machine type communications, and new MAC and higher-layer procedures provided by extended discontinuous reception. We also briefly discuss the narrowband IoT, which is in the development stage with a target completion date of June 2016.

An overview of 3GPP enhancements on machine to machine communications

Systems and methods for facilitating inter-cell interference coordination using resource partitioning are described. A UE may receive or determine information related to received interference and/or future scheduling. The information may be communicated to a serving base station, which may use the information to allocate uplink or downlink resources between cells. The uplink and/or downlink resource may be partitioned in subbands to mitigate interference from adjacent network nodes. The eNBs may communicate, such as directly, via a backhaul connection, and/or between UEs to configure interference coordination and signaling.

Methods and apparatus for facilitating inter-cell interference coordination via over the air load indicator and relative narrowband transmit power

Methods and apparatus for partitioning resources for enhanced inter-cell interference coordination (eICIC) are provided. Certain aspects involve broadcasting a message indicating time-domain resource partitioning information (RPI), where a user equipment (UE) may be operating in idle mode. With the RPI, the UE may be able to identify protected resources with reduced/eliminated interference from neighboring cells. The RPI in this broadcasted message may be encoded as a bitmap as an alternative or in addition to enumeration of the U/N/X subframes. Other aspects entail transmitting a dedicated or unicast message indicating the time-domain RPI, where a UE may be operating in connected mode. With the RPI, the UE may be able to determine channel state information (CSI), make radio resource management (RRM) measurements, or perform radio link monitoring (RLM), based on one or more signals from a serving base station during the protected time-domain resources.

Resource Partitioning Information for Enhanced Interference Coordination

Methods and apparatus for supporting adaptive resource negotiation between evolved node Bs (eNBs) for enhanced inter-cell interference coordination (eICIC) are provided. This resource negotiation may occur via a network backhaul between the eNBs or, in some cases, using over-the-air messages (OAMs). For certain aspects, a first eNB may propose its adaptive resource partitioning information (ARPI) to a second eNB, where the second eNB may accept or reject the proposed resource partitioning. If the second eNB accepts the proposed partitioning, the second eNB may schedule resources, such as subframes, based on the accepted partitioning.

Madhavan Srinivasan Vajapeyam

Papers

A survey on 3GPP heterogeneous networks

An overview of 3GPP enhancements on machine to machine communications

Methods and apparatus for facilitating inter-cell interference coordination via over the air load indicator and relative narrowband transmit power

Resource Partitioning Information for Enhanced Interference Coordination

Adaptive resource negotiation between base stations for enhanced interference coordination