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

There is disclosed a method of operating a user equipment in a radio access network, the user equipment being configured with a transmission resource pool. The transmission resource pool includes resources for transmission of response control signaling by the user equipment. The method includes transmitting response control signaling utilising a resource structure, the resource structure being selected from the transmission resource pool based on a signaling characteristic of characterising signaling, the resource structure further being selected based on selection control information included in a received selection control message. The disclosure also pertains to related devices and methods.

Resource selection for control signaling in a radio access network

Radio resources are allocated to communication between a mobile station (40) and a base station (20). The available set of radio resources may comprise radio resources primarily assigned to a neighbouring cell if the 5 mobile station (40) experience an instantaneous low level of co-channel interference from such neighbouring cells. The existence of interference is preferably deduced from signal quality measurements of pilot signals. The allocation may concern uplink and/or downlink (54) communication. Devices (41) for performing the measurements are located in the mobile station (40), while devices for performing the evaluation (22), selection (23) and actual allocation (24) can be placed in different parts of the communications system- in the mobile station (40), in a base station (20) or In a core network node (70), or as a distributed means.

Attribution dynamique de ressources radio

A method for controlling the transmission power in a mobile terminal (200) in a wireless communication system in which a transmission bandwidth allocated for transmissions by the mobile terminal (200) is variable by transmission, the method comprising receiving (310) a plurality of transmission power control orders, each transmission power control order administering an adjustment in the transmission power related to a previous transmission of the mobile terminal (200); characterized in that the method further comprises: when the mobile terminal is in a state of power limitation that requires the mobile terminal to transmit at its maximum transmission power: - adjust (350) a cumulative power control value when a control order of received transmission power administers a negative adjustment in the transmission power; - ignoring a transmission power control order received when the transmission power control order received administers a positive adjustment in transmission power, so that the accumulated power control value is not adjusted when the control order of received transmission power administers a positive adjustment in transmission power; and - calculate (360) respective transmission power settings for each transmission by the mobile terminal (200) as the lower of the maximum transmission power for the mobile terminal and the transmitter output power calculated based on the bandwidth assigned for the transmission and the accumulated power control value.

Uplink power control for limited power terminals

Following the standardization of WCDMA in early 2000, it was soon recognized that the existing 3G technology would need to evolve to meet the challenges of the era of mobile broadband. Shifts in technology, user behavior, traffic models, business models, and the learning curve of the early phases of 3G deployment drove a research effort that lead to the evolution from the release 99 specifications to modern HSPA. Today, HSPA stands alongside LTE as one of 3GPP’s market-leading air interfaces, capable of around 346 Mbps in downlink and 34 Mbps in uplink. With around two billion subscribers worldwide in 2014, demand for traffic and technology evolution in HSPA continues to grow. This chapter provides an overview of the HSPA evolution path over 3GPP releases 5 to 11 by describing each of the main building blocks.

Introduction to HSPA

Publisher Summary
This book describes the evolution of 3G mobile systems from wideband code division multiple access (WCDMA) to High-Speed Packet Access (HSPA) and its continued evolution, and finally the 3G Long-Term evolutions. The technology evolution does not stop with HSPA Evolution and Long-Term Evolution (LTE). The technology race for the next generation of mobile communication has already started with regulatory bodies, standards organizations, market forums, research bodies and, other bodies taking various initiatives. The chapter focuses on IMT-Advanced, the research community, and the standardization bodies. While LTE standardization is not yet completely finalized, the race for the next radio interface is already ongoing. Many activities are initiated in the research community and some standardization developing organizations are about to start (their work towards IMT-Advanced. However, IMT-Advanced is still several years away whereas HSPA Evolution and LTE are just around the corner. The chapter concludes that HSPA evolution is built as a continuing evolution of the existing WCDMA/HSPA technology whereas LTE is a new radio access optimized purely for IP based traffic. These two technologies promise to give more services, capabilities, and performance to the end users than any other radio interface technology has been able to do to date.

Stefan Parkvall

Papers

Resource selection for control signaling in a radio access network

Attribution dynamique de ressources radio

Uplink power control for limited power terminals

Introduction to HSPA

21 – Future evolution