Wireless Communications

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

Multiple-input multiple-output (MIMO) technology is maturing and is being incorporated into emerging wireless broadband standards like long-term evolution (LTE) [1]. For example, the LTE standard allows for up to eight antenna ports at the base station. Basically, the more antennas the transmitter/receiver is equipped with, and the more degrees of freedom that the propagation channel can provide, the better the performance in terms of data rate or link reliability. More precisely, on a quasi static channel where a code word spans across only one time and frequency coherence interval, the reliability of a point-to-point MIMO link scales according to Prob(link outage) ` SNR-ntnr where nt and nr are the numbers of transmit and receive antennas, respectively, and signal-to-noise ratio is denoted by SNR. On a channel that varies rapidly as a function of time and frequency, and where circumstances permit coding across many channel coherence intervals, the achievable rate scales as min(nt, nr) log(1 + SNR). The gains in multiuser systems are even more impressive, because such systems offer the possibility to transmit simultaneously to several users and the flexibility to select what users to schedule for reception at any given point in time [2].

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Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays

The quintessential goal of sensor array signal processing is the estimation of parameters by fusing temporal and spatial information, captured via sampling a wavefield with a set of judiciously placed antenna sensors. The wavefield is assumed to be generated by a finite number of emitters, and contains information about signal parameters characterizing the emitters. A review of the area of array processing is given. The focus is on parameter estimation methods, and many relevant problems are only briefly mentioned. We emphasize the relatively more recent subspace-based methods in relation to beamforming. The article consists of background material and of the basic problem formulation. Then we introduce spectral-based algorithmic solutions to the signal parameter estimation problem. We contrast these suboptimal solutions to parametric methods. Techniques derived from maximum likelihood principles as well as geometric arguments are covered. Later, a number of more specialized research topics are briefly reviewed. Then, we look at a number of real-world problems for which sensor array processing methods have been applied. We also include an example with real experimental data involving closely spaced emitters and highly correlated signals, as well as a manufacturing application example.

Two decades of array signal processing research: the parametric approach

It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

Our society is undergoing an unprecedented transformation as more and more devices are being interconnected over the wide area network. This will profoundly change our productivity and human interaction. The Internet of Things (IoT) has been one of the most successful growth segments in cellular-based applications in recent years, with an annual growth rate in the range of 30 percent. It is anticipated that the ratio of connected things to people will rise sharply over the next 5-10 years, to around 7:1 or even higher, which means that there would be 50 billion or even more connected things. The GSM Association believes the number could grow to 24 billion by 2020 [1], while Gartner forecasts that number to be 35 billion [2]. Applications include smart building, smart metering, smart city, ehealth, smart environment, consumer electronics, and telematics/vehicle to everything (V2X). Consequently, this part of the Feature Topic will focus on technologies for Long Term Evolution (LTE) that will enhance the support of IoT.

LTE-advanced pro: part 2 [Guest Editorial]

A method and a radio base station for interleaving control channel data to be transmitted in a telecommunications system are described The method comprises grouping the control channel elements CCEl- CCEn into a first order of control channel symbol groups, determining a number of available symbol group positions of control channel transmission resources, adding symbol groups comprising 'dummy' values or zeros to the first order of control channel symbol groups, interleaving the first order of the control channel symbol groups resulting in an a second order, cyclic shifting the second order and mapping the cyclic shifted second order of control channel symbol groups to the control channel transmission resources

Interference randomisation of control channel elements

This chapter provides a detailed description of the LTE downlink physical-layer functionality, including transport-channel processing, downlink reference signals, details on downlink multi-antenna transmission, and control signaling.

Downlink Physical-Layer Processing

Embodiments include a method for assigning, to a user equipment (UE) in a wireless communication network, frequency-domain resources of a communication channel shared with one or more further UEs. Such embodiments include sending, to the UE, an indication of an active carrier bandwidth part (BWP) usable for communicating via the shared channel. Such embodiments include selecting one or more frequency-domain resource blocks (RBs), within the active BWP, to be assigned to the UE. Such embodiments include encoding an indication of the one or more selected RBs using a plurality of available bits, wherein the plurality of available bits is insufficient to encode all assignable combinations of RBs within the active BWP. Such embodiments include sending the encoded indication to the UE via a downlink control channel. Embodiments also include complementary methods performed by a UE, as well as network nodes and UEs configured and/or arranged to perform various methods.

Signalling of frequency-domain resource assignment

The problem of data transmission over an unknown channel is considered and an approach to code design for joint channel estimation, equalization and error correction is proposed. In contrast to most traditional approaches, where the receiver is designed given knowledge of the code used at the transmitter, this paper proposes an approach where the code is designed based on knowledge of the receiver structure and the statistical properties of the channel.

Stefan Parkvall

Papers

LTE-advanced pro: part 2 [Guest Editorial]

Interference randomisation of control channel elements

Downlink Physical-Layer Processing

Signalling of frequency-domain resource assignment

Code design for combined channel estimation and error correction coding