Cellular networks are usually modeled by placing the base stations on a grid, with mobile users either randomly scattered or placed deterministically. These models have been used extensively but suffer from being both highly idealized and not very tractable, so complex system-level simulations are used to evaluate coverage/outage probability and rate. More tractable models have long been desirable. We develop new general models for the multi-cell signal-to-interference-plus-noise ratio (SINR) using stochastic geometry. Under very general assumptions, the resulting expressions for the downlink SINR CCDF (equivalent to the coverage probability) involve quickly computable integrals, and in some practical special cases can be simplified to common integrals (e.g., the Q-function) or even to simple closed-form expressions. We also derive the mean rate, and then the coverage gain (and mean rate loss) from static frequency reuse. We compare our coverage predictions to the grid model and an actual base station deployment, and observe that the proposed model is pessimistic (a lower bound on coverage) whereas the grid model is optimistic, and that both are about equally accurate. In addition to being more tractable, the proposed model may better capture the increasingly opportunistic and dense placement of base stations in future networks.

A Tractable Approach to Coverage and Rate in Cellular Networks

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

Femtocells, despite their name, pose a potentially large disruption to the carefully planned cellular networks that now connect a majority of the planet's citizens to the Internet and with each other. Femtocells - which by the end of 2010 already outnumbered traditional base stations and at the time of publication are being deployed at a rate of about five million a year - both enhance and interfere with this network in ways that are not yet well understood. Will femtocells be crucial for offloading data and video from the creaking traditional network? Or will femtocells prove more trouble than they are worth, undermining decades of careful base station deployment with unpredictable interference while delivering only limited gains? Or possibly neither: are femtocells just a "flash in the pan"; an exciting but short-lived stage of network evolution that will be rendered obsolete by improved WiFi offloading, new backhaul regulations and/or pricing, or other unforeseen technological developments? This tutorial article overviews the history of femtocells, demystifies their key aspects, and provides a preview of the next few years, which the authors believe will see a rapid acceleration towards small cell technology. In the course of the article, we also position and introduce the articles that headline this special issue.

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Femtocells: Past, Present, and Future

The proliferation of internet-connected mobile devices will continue to drive growth in data traffic in an exponential fashion, forcing network operators to dramatically increase the capacity of their networks. To do this cost-effectively, a paradigm shift in cellular network infrastructure deployment is occurring away from traditional (expensive) high-power tower-mounted base stations and towards heterogeneous elements. Examples of heterogeneous elements include microcells, picocells, femtocells, and distributed antenna systems (remote radio heads), which are distinguished by their transmit powers/ coverage areas, physical size, backhaul, and propagation characteristics. This shift presents many opportunities for capacity improvement, and many new challenges to co-existence and network management. This article discusses new theoretical models for understanding the heterogeneous cellular networks of tomorrow, and the practical constraints and challenges that operators must tackle in order for these networks to reach their potential.

Heterogeneous cellular networks: From theory to practice

The present invention is designed to provide a user terminal, a radio base station and a radio communication method of novel structures that can achieve a good communication environment. A radio base station non-orthogonal-multiplexes downlink signals for a plurality of user terminals over a given radio resource, a user terminal having received the downlink signals for the plurality of user terminals decodes downlink signal for another user terminal, judges whether or not the downlink signal for the other user terminal has been successfully received, based on the decoding result of the downlink signal, reports a judgement result as to whether or not the downlink signal for the other user terminal has been successfully received and a judgement result as to whether or not a downlink signal for the user terminal has been successfully received, to the radio base station, and then the radio base station executes retransmission control of downlink signals based on reports from the user terminal.

User terminal, radio base station and radio communication method

This article provides an overview of contemporary and forward looking inter-cell interference coordination techniques for 4G OFDM systems with a specific emphasis on implementations for LTE. Viable approaches include the use of power control, opportunistic spectrum access, intra and inter-base station interference cancellation, adaptive fractional frequency reuse, spatial antenna techniques such as MIMO and SDMA, and adaptive beamforming, as well as recent innovations in decoding algorithms. The applicability, complexity, and performance gains possible with each of these techniques based on simulations and empirical measurements will be highlighted for specific cellular topologies relevant to LTE macro, pico, and femto deployments for both standalone and overlay networks.

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Interference coordination and cancellation for 4G networks

A mobile station receives a downlink control structure in a first carrier, where the downlink control structure indicates that control information for the mobile station is on a second, different carrier. The mobile station decodes the control information in the second carrier, where the control information specifies resource allocation of a wireless link for the mobile station. More specifically, according to some implementations, the control channel in the first carrier specifies the resource allocation for an extended control channel in the second carrier, where the extended control channel specifies the resource allocation for traffic data of a wireless link for the mobile station.

Providing a downlink control structure in a first carrier to indicate control information in a second, different carrier

Precoding for multiple-input multiple-output (MIMO) spatial multiplexing generally requires high feedback overhead and/or high-complexity processing. Simultaneous reduction in transmitter complexity and feedback overhead is proposed by imposing a diagonal structural constraint to precoding, i.e., power allocation. Minimum bit-error rate (MBER) is employed as the optimization criterion, and an approximate MBER (AMBER) power-allocation algorithm is proposed for a variety of receivers, including zero-forcing (ZF), successive interference cancellation (SIC), and ordered SIC (OSIC). While previously proposed precoding schemes either require ZF equalization for MBER, or use a minimum mean-squared error (MMSE) criterion, we provide a unified MBER solution to power allocation for ZF, SIC, and OSIC receiver structures. Improved error-rate performance is shown both analytically and by simulation. Simulation results also indicate that SIC and OSIC with AMBER power allocation offer superior performance over previously proposed MBER precoding with ZF equalization, as well as over MMSE precoding/decoding. Performance under noisy channels and power feedback is analyzed. A modified AMBER algorithm that mitigates error propagation in interference cancellation is developed. Compared with existing precoding methods, the proposed schemes significantly reduce both transmit processing complexity and feedback overhead, and improve error-rate performance

Approximate Minimum BER Power Allocation for MIMO Spatial Multiplexing Systems

Power allocation for multiple-input multiple-output (MIMO) spatial multiplexing systems is investigated. Minimization of bit error rate (MBER) is employed as the optimization criterion. MBER power allocation schemes for a variety of receiver structures, including zero-forcing (ZF), successive interference cancellation (SIC), and ordered SIC (OSIC), are proposed. It is shown that the newly proposed MBER power allocation schemes improve error rate performance. Simulation results indicate that SIC and OSIC with MBER power allocation outperform MBER precoding for ZF equalization as well as minimum mean squared-error (MMSE) preceding/decoding. Performance under noisy channels and power feedback is analyzed. A modified algorithm that mitigates error propagation in interference cancellation is developed. Compared to existing precoding methods, the proposed schemes significantly reduce both processing complexity and feedback overhead, and improve error rate performance.

Minimum BER power allocation for MIMO spatial multiplexing systems

Neighbor cell hearability can be improved by including an additional reference signal that can be detected at a low sensitivity and a low signal-to-noise ratio, by introducing non-unity frequency reuse for the signals used for a time difference of arrival (TDOA) measurement, e.g., orthogonality of signals transmitted from the serving cell sites and the various neighbor cell sites. The new reference signal, called the TDOA-RS, is proposed to improve the hearability of neighbor cells in a cellular network that deploys 3GPP EUTRAN (LTE) system, and the TDOA-RS can be transmitted in any resource blocks (RB) for PDSCH and/or MBSFN subframe, regardless of whether the latter is on a carrier supporting both PMCH and PDSCH or not. Besides the additional TDOA-RS reference signal, an additional synchronization signal (TDOA-sync) may also be included to improve the hearability of neighbor cells.

Neng Wang

Papers

Interference coordination and cancellation for 4G networks

Providing a downlink control structure in a first carrier to indicate control information in a second, different carrier

Approximate Minimum BER Power Allocation for MIMO Spatial Multiplexing Systems

Minimum BER power allocation for MIMO spatial multiplexing systems

Method and System for User Equipment Location Determination on a Wireless Transmission System