A cellular base station serves a multiplicity of single-antenna terminals over the same time-frequency interval. Time-division duplex operation combined with reverse-link pilots enables the base station to estimate the reciprocal forward- and reverse-link channels. The conjugate-transpose of the channel estimates are used as a linear precoder and combiner respectively on the forward and reverse links. Propagation, unknown to both terminals and base station, comprises fast fading, log-normal shadow fading, and geometric attenuation. In the limit of an infinite number of antennas a complete multi-cellular analysis, which accounts for inter-cellular interference and the overhead and errors associated with channel-state information, yields a number of mathematically exact conclusions and points to a desirable direction towards which cellular wireless could evolve. In particular the effects of uncorrelated noise and fast fading vanish, throughput and the number of terminals are independent of the size of the cells, spectral efficiency is independent of bandwidth, and the required transmitted energy per bit vanishes. The only remaining impairment is inter-cellular interference caused by re-use of the pilot sequences in other cells (pilot contamination) which does not vanish with unlimited number of antennas.

Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas

Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

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.

/pdf/femtocells-past-present-and-future-di96bi1e7j.pdf

Femtocells: Past, Present, and Future

With the exponential increase in mobile internet traffic driven by a new generation of wireless devices, future cellular networks face a great challenge to meet this overwhelming demand of network capacity. At the same time, the demand for higher data rates and the ever-increasing number of wireless users led to rapid increases in power consumption and operating cost of cellular networks. One potential solution to address these issues is to overlay small cell networks with macrocell networks as a means to provide higher network capacity and better coverage. However, the dense and random deployment of small cells and their uncoordinated operation raise important questions about the energy efficiency implications of such multi-tier networks. Another technique to improve energy efficiency in cellular networks is to introduce active/sleep (on/off) modes in macrocell base stations. In this paper, we investigate the design and the associated tradeoffs of energy efficient cellular networks through the deployment of sleeping strategies and small cells. Using a stochastic geometry based model, we derive the success probability and energy efficiency in homogeneous macrocell (single-tier) and heterogeneous K-tier wireless networks under different sleeping policies. In addition, we formulate the power consumption minimization and energy efficiency maximization problems, and determine the optimal operating regimes for macrocell base stations. Numerical results confirm the effectiveness of switching off base stations in homogeneous macrocell networks. Nevertheless, the gains in terms of energy efficiency depend on the type of sleeping strategy used. In addition, the deployment of small cells generally leads to higher energy efficiency but this gain saturates as the density of small cells increases. In a nutshell, our proposed framework provides an essential understanding on the deployment of future green heterogeneous networks.

Energy Efficient Heterogeneous Cellular Networks

Two-tier networks, comprising a conventional cellular network overlaid with shorter range hotspots (e.g. femtocells, distributed antennas, or wired relays), offer an economically viable way to improve cellular system capacity. The capacity-limiting factor in such networks is interference. The cross-tier interference between macrocells and femtocells can suffocate the capacity due to the near-far problem, so in practice hotspots should use a different frequency channel than the potentially nearby high-power macrocell users. Centralized or coordinated frequency planning, which is difficult and inefficient even in conventional cellular networks, is all but impossible in a two-tier network. This paper proposes and analyzes an optimum decentralized spectrum allocation policy for two-tier networks that employ frequency division multiple access (including OFDMA). The proposed allocation is optimal in terms of area spectral efficiency (ASE), and is subjected to a sensible quality of service (QoS) requirement, which guarantees that both macrocell and femtocell users attain at least a prescribed data rate. Results show the dependence of this allocation on the QoS requirement, hotspot density and the co-channel interference from the macrocell and femtocells. Design interpretations are provided.

Spectrum allocation in tiered cellular networks

Apparatus and methods for accessing a wireless telecommunications network by transmitting a random access signal. The random access signal includes a random access preamble signal selected from a set of random access preamble signals constructed by cyclically shift selected root CAZAC sequences. The random access signal may be one or more transmission sub-frames in duration, the included random access preamble sequence's length being extended with the signal to provide improved signal detection performance in larger cells and in higher interference environments. The random access signal may include a wide-band pilot signal facilitating base station estimation of up-link frequency response in some situations. Each of the plurality of available random access preamble sequences may be assigned a unique information value. The base station may use the information encoded in the random access preamble to prioritize responses and resource allocations. Random access signal collisions are dealt with by a combination of preamble code space randomness and back-off procedures.

Random access structure for wireless networks

Embodiments of the invention provide method for allocating CAZAC pilot (reference signal) sequences in multiple access OFDMA systems, or alternatively, in multiple access DFT-spread OFDM(A) systems (or SC-FDMA). Reference signal transmissions from different mobiles can either be distinguished by use of disjoint sub-carriers (frequency division orthogonality), or alternatively by use of distinct cyclic shifts of one base CAZAC sequence. In a wireless cellular network, neighboring cells should utilize different CAZAC sequences, in order to mitigate out-of-cell interference.

Reference Signal Sequences and Multi-User Reference Signal Sequence Allocation

Embodiments of the invention provide method and structure for boosting pilot signal power relative to data signal power. The velocity of user equipment is obtained. The velocity measurement is used in determining the transmission power of the pilot signal and applying the increase to a plurality of pilots and decreasing the data signal power by a proportional amount.

Pilot Channel Design for Communication Systems

Methods and apparatus to allocate reference signals in wireless communication systems are disclosed. A disclosed example apparatus comprises a reference signal generator (501) to generate a reference sequence (505) based on a parameter assigned to a wireless region, wherein the parameter specifies a first reference sequence to be transmitted by a first device of the wireless region during a first time interval, the first reference sequence being different from a second reference sequence assigned to a second device of a second wireless region adjacent to the first wireless region. The reference sequence generator comprises a cyclic shift selector (503) to select a cyclic shift for the first time interval based on the parameter and a cyclic shifter (506) to cyclically shift the first reference signal based on the selected cyclic shift. The example apparatus further comprises a transmit adapter (510) to transmit the cyclically shifted first reference sequence.

Methods and apparatus to allocate reference signals in wireless communication systems

Transmitting an ACWNACK response in a wireless cellular network by mapping the data value into a cyclic shifted version of a reference signal. A subframe is formed (704) with a plurality of symbols with certain symbols designated as reference signal (RS) symbols. The receiver and transmitter both know when an ACWNACK response is expected. If an ACWNACK response is not expected (706), then an RS is inserted (708) in the duration of symbols designated as RS symbols. If an ACWNACK response is expected, then the ACWNACK response is embedded (7 10) in one or more of the symbols designated as RS symbols. The subframe is transmitted (712) to a receiver, and the receiver can determine the ACWNACK value in the RS symbol, if present, and also use the RS symbol for coherent demodulation of a CQI (channel quality indicator) or data.

Transmission of ack/nack bits and their embedding in the reference signal

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