MIMO (multiple-input multiple-output)

http://www.signal.uu.se/Research/rdiversity.html

http://www.networkworld.com/details/6830.html

A technique for boosting wireless bandwidth and range by taking advantage of multiplexing.

MIMO algorithms in a radio chipset send information out over two or more antennas. The radio signals reflect off objects, creating multiple paths that in conventional radios cause interference and fading. But MIMO uses these paths to carry more information, which is recombined on the receiving side by the MIMO algorithms

Many wireless-LAN vendors expect that some form of MIMO will be the basis of work just starting in the IEEE 802.11n Task Group, which is creating a specification for WLANs having at least 100M bit/sec throughput. The 3rd Generation Partnership Project, a collaboration of telecom standards groups, also is evaluating MIMO techniques for use in cellular networks.

MIMO doubles the spectral efficiency compared with that of current WLANs. The maximum data rate for 802.11g and 802.11a networks is 54M bit/sec, though actual throughput is closer to 20M to 30M bit/sec. Current MIMO techniques can boost raw WLAN throughput to 108M bit/sec, supporters say.

In communication theory, MIMO refers to radio links with multiple antennas at the transmitter and the receiver side. Given multiple antennas, the spatial dimension can be exploited to improve the performance of the wireless link. The performance is often measured as the average bit rate (bit/s) the wireless link can provide or as the average bit error rate (BER). Which one has most importance depends on the application.

Given a MIMO channel, duplex method and a transmission bandwidth, the system can be categorized as

·         Flat or frequency selective fading
·        With full, limited or without transmitter channel state information (CSI)

Where full CSI means the knowledge of the complete MIMO channel transfer function. In a TDD system with a duplex time less than the coherence time of the channel, full CSI is available at the transmitter, since then, the channel is reciprocal. In FDD systems, there commonly exists a feedback channel from the receiver to the transmitter that provides the transmitter with some partial CSI. This could be information of which subgroup of antennas to be used or which eigenmode of the channel that is strongest. It is also possible to achieve a highly robust wireless link without any CSI at the transmitter, by using transmit diversity. Diversity can be achieved through so called space-time codes, like the Alamouti code for two transmit antennas and high bit rates is achieved by spatial multiplexing systems, such as the pioneer system from Bell Labs abbreviated as BLAST.

If a broadband wireless connection is desired, the symbol rate must be increased further which at some point will lead to a frequency selective channel. Then, there are two ways to go, either we employ pre- or post-equalization of the channel or we divide the channel into many narrowband flat fading sub-channels, a technique utilized by OFDM, and transmit our data on these sub streams, without the need for channel equalization. Hence, it is always possible to convert a frequency selective channel to many flat fading channels using OFDM and apply the developed flat fading MIMO signalling techniques to each of these sub-channels.

When full CSI is available at the transmitter, it is possible to transmit data on the MIMO channel eigenmodes. A MIMO system with N transmit antennas and M receive antennas has min(N,M) eigenmodes. The gain of these eigenmodes is proportional to the singular values of the MIMO channel, so they have disparate power

Algorithms for Combined Spatial and Temporal Equalization in TDMA

The received baseband signal in a TDMA cellular system is corrupted by noise, by intersymbol interference due to multipath propagation and by co-channel interference from other users.

If only one antenna element is available at the receiver one can use filtering of the received time series in order to estimate the transmitted sequence, i.e. temporal equalization. If several antenna elements are available, it becomes possible to perform spatial filtering by forming beams in the direction of a desired signal. Noise and interference and also delayed signals which would result in intersymbol interference, can then be suppressed if they arrive from other directions.

The beamforming concept can be combined with temporal equalization, resulting in spatio-temporal equalization. It then becomes possible to make effective use of the energy in delayed signals arriving from several directions, while suppressing the signals from co-channel interferers.

Spatio-temporal equalization can be performed by generalizing the single-input-single-output (SISO) DFE to a multiple-input-single-output (MISO) DFE. One can also use a MLSE Viterbi detector.

A MISO DFE will, by necessity, contain a larger number of adjustable parameters than a SISO DFE. This leads to two potential problems.

• The adjustment of many filter parameters, based on short training sequences, is sensitive to noise. Misadjustment may lead to poor performance.
• The computational complexity of the algorithm will increase.

The use of arrays of antenna elements is practical at the base station, but much less practical at the mobile. The investigated techniques are therefore primarily applicable in the transmission from the mobiles to the base stations.

Channel reuse within cell

In a TDMA system, the combination of a certain time slot and a certain frequency is called a channel. In a cellular system, every channel is used by multiple base stations. However, due to interference from one base station to another, not all channels are used in all cells. Instead, channels are reused at a certain interval. The interval with which the channels are reused is called the reuse distance. In a GSM system, the reuse distance is between 9 and 30.

In the future, the spatial dimension must be exploited more thoroughly. The first step is of course to decrease the reuse distance. This is the primary objective for the algorithms described above. If every channel could be used in each cell, the system capacity would rise by a factor equal to the reuse distance in the current system. But if an even larger increase in capacity is desired, we have to lower the reuse distance below one or, in other words, perform channel reuse within cell.