International telecommunication union
Spectral efficiency gains in an interference limited cellular system
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- 5 Variation in spectrum efficiency gains using MIMO techniques for different scattering environments
- 6 Variation of MIMO link capacity within a cellular network
- 7 Implementation issues
4 Spectral efficiency gains in an interference limited cellular systemFigure 17 shows the spectrum efficiency that can be achieved based on Shannon capacity [2]. The number of antennas at the base station and each terminal are equal. Similar related results for an intereference limited mobile network environment can be found in [8]. FIGURE 17
5 Variation in spectrum efficiency gains using MIMO techniques for different scattering environmentsIn order to achieve the potential gains of MIMO systems it is necessary to have a complex scattering environment and so it is essential to quantify the gains for different scattering environments. A simple demonstration of the gains possible is shown in Fig. 18 where the results are shown of some simulations of the spectral efficiency achievable for a single link of a mobile system operating in a range of scattering environments. The simulated environments are modelled as Rician channels with a range of K factors to cover the cases from fairly clear line of sight (K > 10) down to rich scattering environments, (K < 0.1). These results were obtained under idealized conditions of perfect channel state information at both the transmitter and receiver at 10 dB SNR. Figure 18
This topic is the focus for a substantial amount of research work, e.g. in [10] and [13] which show that the distribution of MIMO capacity for classical Rayleigh channels tends towards a Gaussian distribution as the number of transmit and receive antennas increases. Simulations in these papers show that the Gaussian approximation to the capacity is reasonably accurate even for systems with three or more antennas at each end of the link and exact expressions for the mean and variance of the Gaussian capacity for any given numbers of transmit and receive antennas are derived in [10]. It is shown [11] that the distribution of MIMO capacity for Rician fading conditions can also be expressed as a Gaussian random variable with a similar dependence on the number of transmit and receive antennas. These topics are further developed in [12] which examines the MIMO capacity under the influence of various power allocation algorithms at the transmitter and it is shown that the Gaussian approximation still holds good for the different power allocation strategies studied. These included equal power for each antenna, the classical “water filling” technique with perfect knowledge of the channel conditions and a new strategy giving better capacity than the first two for less than ideal estimates of the channel conditions. All of these power allocation methods are shown to give link capacity that can still be approximated by a single Gaussian random variable for both Rayleigh and Rician fading channels. 7 Implementation issuesThe introduction of MIMO techniques into wireless communication systems introduces a number of implementation challenges. At the base station the greatest impact is likely to be in the increased RF and cabling requirements due to the increased number of transmit/receive antenna elements until more integrated antenna, receiver, transmitter structures are developed. The greatest challenges, however, lie within the terminal where the size, power and cost constraints must be overcome. Research initiatives must address the viability of terminals employing MIMO or diversity techniques, with particular emphasis being placed on maximizing the performance of the terminal antenna system in realistic macrocellular deployment scenarios and within the restricted form factors of future terminals such as laptops, PDAs and handsets. Key challenges will include the design of antennas with low correlation within such a confined space and good performance in realistic indoor and outdoor nomadic and mobile propagation environments and the difficulties of minimizing interactions between different functions within the terminal (EMC). Diverse terminal antennas have already been investigated for various form factors, including picocell base units [14] and [15] and fixed wireless access terminals [16]. In the first two cases the antennas are purely internal to a standard housing, while in the third the terminal form factor was adapted to enable best antenna performance. Both of these approaches are options for future implementations of diverse/MIMO terminal antennas. In the context of a free-standing terminal, e.g. a laptop, an important aspect is whether the terminal antenna elements are flat on a table (e.g. in the base unit) or vertically oriented (in the display), and making the design robust against several deployments is part of the challenge [14] and [15]. A key element in the development of MIMO antenna systems is optimization of the design to work in the MIMO propagation channels of the target deployment scenarios. The MIMO propagation channel is a current study area in both 3GPP and 3GPP2 standards organizations, with a series of submissions from various companies. Also, the COST 259 [18] research project team has used various propagation measurement results to arrive at an outdoors-to-outdoors channel model, and COST 273 [19] aims to extend this work, with subgroup activities including MIMO systems, handset antennas, channel measurements and channel modelling. It is expected that ongoing research by the industry will yield results in the following areas: i) MIMO propagation channel models for macro-, micro-, and picocellular deployment scenarios which are sufficiently detailed to allow theoretical evaluation of MIMO/diversity terminal antenna configurations. ii) Generic antenna system designs for laptops, PDAs, stand-alone units, and handsets. iii) Understanding of the interaction between multi-element antenna design and the complex localized propagation environment. iv) Designing efficient signal processing algorithms and associated coding schemes which achieve much of the capacity gains allowed by the theory, but which can be implemented with much lower levels of processing power [9]. There are clearly substantial implementation issues to be solved before MIMO techniques can used to increase the capacity of mobile communication networks. However, it is useful to consider the complexity of achieving high data rates within the same channel bandwidth using conventional high order modulation schemes. For a MIMO link using [4,4] antennas and 4 state modulation the equivalent single channel link would need to use a 256-point modulation constellation for the same symbol rate. With a not unreasonable 16-point modulation on the [4,4] MIMO system it would be necessary to implement a somewhat unrealistic 4 096 point modulation on the single high-speed channel. Directory: dms pub -> itu-r -> oth oth -> Section 1a vocabulary, characteristics and general technologies for land mobile service oth -> U. S. Mobile eas for atsc mobile dtv itu-r -> Report itu-r sa. 2312-0 (09/2014) itu-r -> Report itu-r itu-r -> 3rd itu inter-regional workshop on wrc-15 preparation geneva, 1 – 3 September 2015 oth -> Radiocommunication Study Groups oth -> Itu-r workshop on Emergency Broadcasting Speakers Biographies Lynn Claudy oth -> Coordination and notification procedures introduction Download 496.69 Kb. Share with your friends:
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