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

Using method and device in wireless cellular system

This chapter describes some of the RF technologies needed at mm-Wave frequencies to implement devices and BS in frequency range 2. Challenges and possibilities are discussed for different implementation alternatives.

RF Technologies at mm-Wave Frequencies

The third-generation WCDMA standard has been enhanced to offer significantly increased performance for packet data and broadcast services through the introduction of high-speed downlink packet access (HSDPA), enhanced uplink, and multimedia broadcast multicast services (MBMS). This article provides an overview of the key technologies used, the reasons behind their selection, and their integration into WCDMA. Performance results are also included to exemplify the performance possible in an evolved WCDMA network.

Evolving technologies for 3g cellular wireless communications systems

The performance of HSPA is driven by a complex mix of aspects such as, among other things, traffic behaviors, connectivity states, user population and positions, propagation environment effects, algorithmic effects, operator policies, intercell and inter-UE interference, signaling error levels, reporting accuracies, and user behavior. These factors interact in a nontrivial manner. A proportion of the factors relate to human behavior. Thus, the performance of an HSPA deployment is never analytically predictable. Nonetheless, statistical analysis and simulation of system behavior is needed for understanding performance drivers and benchmarking improvements. To properly characterize HSPA performance in terms of capacity and user experience, it is necessary to model system behavior to some extent. In this context, the term “system” refers to the interaction of all factors that impact capacity and user experience. This chapter reviews the principles behind modeling HSPA performance, the factors that drive performance, and the performance observed when modeling typical deployments.

HSPA system performance

There is disclosed a method of operating a transmitting node in a millimeter-wave communication network. The method comprises transmitting communication signaling in a transmission timing structure, the communication signaling comprising control signaling and data signaling, the communication signaling further comprising reference signaling common to the control signaling and data signaling. The disclosure also pertains to related devices and methods.

Stefan Parkvall

Papers

Using method and device in wireless cellular system

RF Technologies at mm-Wave Frequencies

Evolving technologies for 3g cellular wireless communications systems

HSPA system performance

Scheduling of dmrs for mmw ran