MIMO schemes in LTE

SU-MIMO (Single User MIMO)

•This is an example of downlink 2x2 single user MIMO with precoding.

•Two data streams are mixed (precoded) to best match the channel conditions.

•The receiver reconstructs the original streams resulting in increased single-user data rates and corresponding increase in cell capacity.

•2x2 SU-MIMO is mandatory for the downlink and optional for the uplink

MU-MIMO (Multiuser MIMO)

•Example of uplink 2x2 MU-MIMO.

•In multiple user MIMO the data streams come from different UE.

•There is no possibility to do precoding since the UE are not connected but the wider TX antenna spacing gives better de-correlation in the channel.

•Cell capacity increases but not the single user data rate.

•The key advantage of MU-MIMO over SU-MIMO is that the cell capacity increase can be had without the increased cost and battery drain of two UE transmitters.

•MU-MIMO is more complicated to schedule than SU-MIMO

Improved Antenna to revolutionise mobile battery life

Atif Shamim, revolutionising mobile battery life

­Atif Shamim, an electronics PhD student at Carleton University, has built a prototype that extends the battery life of mobile phones, by getting rid of all the wires used to connect the electronic circuits with the antenna.

The invention involves a packaging technique to connect the antenna with the circuits via a wireless connection between a micro-antenna embedded within the circuits on the chip.

“This has not been tried before - that the circuits are connected to the antenna wirelessly. They’ve been connected through wires and a bunch of other components. That’s where the power gets lost,” Mr. Shamim said.

He estimates his module consumes 12 times less power than the traditional, wired-transmitter module. It is also much simpler in design, lowering the overall cost of any hand-held device, he said.

Mr. Shamim has filed patent applications in the U.S. and in Canada.

Earlier this year, the Ottawa Centre for Research and Innovation honoured Mr. Shamim and Mr. Arsalan as student researchers of the year for their work in the field of wireless biomedical sensors.

Shamim says his major goals for the innovation still lie in biomedical applications, including his original radiation sensors as well as remote healthcare sensors to monitor heart-rate, blood pressure and body temperature. He and Arsalan have also started up a company called Vital Signs Monitoring, and the two have already filed patents for the technology they developed. Clearly he has come a long way from when he first came to Canada, but he says his goals are still the same.

"My aim when I came here was to get some real skills in this domain, learn some new things and be an expert of something that would be valuable for me to find employment," said Shamim. "I was looking for a neat application for these small transmitters. ...That's where the trend is: make it cheaper, smaller, more efficient, so I think this is a good step towards that."

Adaptive Antenna System

Whenever we talk about the evolution of new technology in telecoms world one thing which always occupy the prominent position is the spectral efficiency. The success and efficiency of any wireless system depends on the spectral efficiency.

What is spectral efficiency though?

Spectral efficiency can be defined as bits/seconds/Hz/cell. It measures how well a wireless network utilizes radio spectrum and also determines the total throughput each base station (cell) can support in a network in a given amount of spectrum.

There is no doubt that if a new air interface is to be build it should be built from the ground up to be optimized for spatial processing. Spectral efficiency directly affects an operator’s cost structure. For a given service and grade of service, it determines the following:

• Required amount of spectrum (CapEx),
• Required number of base stations (CapEx, OpEx),
• Required number of sites and associated site maintenance (OpEx), and,
• Ultimately, consumer pricing and affordability

Spectral efficiency will become even more important as subscriber penetration increases, per-user data rates increase and the as quality of service (esp. data) requirements increase.

There are so many elements for design to achieve high spectral efficiency. Adaptive Antenna System (AAS) is one of the methods to achieve high spectral efficiency.

Adaptive Antenna System (AAS) provides gain and interference mitigation leading to improved signal quality and spectral efficiency.

The use of adaptive antenna systems enables the network operators to increase the wireless network capacity, where such networks are expected to experience an enormous increase in the traffic. This is due to the increased number of users as well as the high data rate service and applications. In addition, adaptive antenna systems offer the potential of increased spectrum efficiency, extended range of coverage and higher rate of frequency reuse.

Adaptive antenna systems consist of multiple antenna elements at the transmitting and/or receiving side of the communication link, whose signals are processed adaptively in order to exploit the spatial dimension of the mobile radio channel. Depending on whether the processing is performed at the transmitter, receiver, or both ends of the communication link, the adaptive antenna technique is defined as multiple-input single-output (MISO), single-input multiple-output (SIMO), or multiple-input multiple-output (MIMO).

Multipath propagation, defined as the creation of multipath signal paths between the transmitter and the receiver due to the reflection of the transmitted signal by physical obstacles, is one of the major problems of mobile communications. It is well known that the delay spread and resulting inter symbol interference (ISI) due to multiple signal paths arriving at the receiver at different times have a critical impact on communication link quality. On the other hand, co-channel interference is the major limiting factor on the capacity of wireless communication systems, resulting from the reuse of the available network resources (e.g., frequency and time) by a number of users.

Adaptive antenna systems can improve link quality by combining the effects of multipath propagation or constructively exploiting the different data streams from different antennas. More specifically, the benefits of adaptive antennas can be summarized as follows:

• Increased range/coverage: the array or beam forming gain is the average increase in signal power at the receiver due to a coherent combination of the signal received at all antenna elements. The adaptive antenna gain compared to a single element antenna can be increased by an amount equal to the number of array elements, e.g., an eight element array can provide a gain of eight (9 dB).
• Increased Capacity: One of the main reasons of the growing interest of adaptive antennas is the capacity increase. In densely populated areas, mobile systems are normally interference-limited; meaning that interference from other users is the main source of noise in the system. This means that the signal to interference ratio (SIR) is much larger than the signal to thermal noise ratio (SNR). Adaptive antennas will on average, increase the SIR. Experimental results report up to 10 dB increase in average SIR in urban areas. For UMTS networks, a fivefold capacity gain has been reported for CDMA.
• Lower power requirements and/or cost reduction: Optimizing transmission toward the wanted user achieves lower power consumption and amplifier costs.
• Improved link quality/reliability: Diversity gain is obtained by receiving independent replicas of the signal through independently fading signal components. Based on the fact that one or more of these signal components will not be in a deep fade, the availability of multiple independent dimensions reduces the effective fluctuations of the signal.
• Increased spectral efficiency: Spectral efficiency is a measure of the amount of information –billable services- that carried by the wireless system per unit of spectrum. It is measured in bits/second/Hertz/cell, thus it includes the effect of multiple access methods, modulation methods, channel organization and resource reuse (e.g., code, timeslot, carrier). Spectral efficiency plays an important role since it directly affects the operator cost structure. Moreover, for a given service and QoS, it determines the required amount of spectrum, the required number of base stations, the required number of sites –and associated site maintenance-, and ultimately, consumer pricing and affordability. Equation (1) shows a simplified formula to estimate the required number of cells per square kilometer. (the offered load is in bits/seconds/km2).
• Security: It is more difficult to tap a connation, since the intruder has to be position himself in the same direction of arrival as the user.
• Reduction of handoff: there is no need for splitting the cells for the sake of capacity increase, and in consequence less amount of handoff.
• Spatial information: the spatial information about the user would be available at any given time, which enables the introduction of Location Based Services.

In addition to the above-mentioned benefits and liken any other systems AAS has got it’s own drawbacks as well. One must point out the following drawbacks (or costs) of the adaptive antennas:

• Transceiver Complexity: It is obvious that the adaptive antenna transceiver is much more complex than the conventional one. This comes from the fact that the adaptive antenna transceiver will need separate transceiver chains for each of the array elements and accurate real-time calibration of each of them.
• Resource Management: Adaptive antennas are mainly a radio technology, but they will also put new demands on network functions such as resource and mobility management. When a new connection is to be set up or the existing connection is to be handed over to a new base station, no angular information is available to the new base station and some means to “find” the mobile station is necessary.
• Physical Size: For the adaptive antenna to obtain a reasonable gain, an array antenna with several elements is necessary. Typically arrays are consisting of six to ten horizontally separated elements have been suggested for outdoor mobile environments. The necessary element spacing is 0.4-0.5 wavelengths. This means that an eight-element antenna would be approximately 1.2 meters wide at 900 MHz and 60 cm at 2 GHz. With a growing public demand for less visible base stations, this size, although not excessive, could provide a problem.

An Adaptive Antenna System (AAS) can focus its transmit energy to the direction of a receiver. While receiving, it can focus to the direction of the transmitting device. The technique used in AAS is known as beamforming or beamsteering or beamshaping. It works by adjusting the width and the angle of the antenna radiation pattern (a.k.a. the beam). Combined with multiple antennas in the Base Station (BS), AAS can be used to serve multiple Subscriber Stations (SSs) with higher throughput. A technique known as SDMA (Space Division Multiple Access) is employed here where multiple SSs that are separated (in space) can transmit and receive at the same time over the same sub-channel.

AAS also eliminates interference to and from other SSs and other sources by steering the nulls to the direction of interferers.AAS is feature suits very well for LTE and it is an optional feature in WiMAX as it yet to be included in WiMAX certification. But due to its effectiveness in improving performance and coverage especially in Mobile WiMAX case, many vendors integrate AAS capability into their products.

Multiuser Cooperative Diversity and Virtual MIMO

MIMO (Multiple Input Multiple Output) by definition requires multiple antenna but it is also possible to use one antenna with Co-operative Diversity to create Cooperative MIMO or Virtual MIMO.

Earlier this year, Nokia Siemens Network reported the following on Virtual MIMO:

Researchers at Nokia Siemens Networks have demonstrated in lab conditions how a virtual Multiple Input Multiple Output (MIMO) technique can be used for the uplink in LTE (Long Term Evolution) networks.

Tests at its labs in Munich, Germany, have shown how, using such an SDMA (Space Division Multiple Access) based technique, two standard mobile devices, each with only one physical transmission antenna, can communicate with a base station simultaneously and on the same radio channel.

On the uplink transmission, data rates of 108Mbit/s were achieved, double the usual speed, while the downlink managed 160Mbit/s.

The researchers say that while MIMO on the downlink primarily generates higher peak data rates for the end user, virtual MIMO on the uplink makes it possible for an operator to increase network capacity and better utilize the available spectrum.

Nokia Siemens also said the technique contributes to one of the crucial prerequisites for the success of LTE by reducing power consumption of LTE based devices to "acceptable levels" even when used for very high data-intensive applications and that this should be achieved at "moderate prices."

The researchers say that with virtual MIMO only one power amplifier and transmission antenna is necessary for each device, contributing to reduced production costs and power needs.

In the LTE test bed, developed and built in collaboration with the Fraunhofer Institute for Telecommunications (Heinrich Hertz Institute), two co-operating end-user devices form a virtual MIMO system in which the antenna elements are distributed over the two devices. The two devices can be supplied simultaneously with data over the same frequency band using space division multiplexing.

The following is an extract from EURASIP Journal onWireless Communications and Networking:

Multihop relaying technology is a promising solution for future cellular and ad hoc wireless communications systems in order to achieve broader coverage and to mitigate wireless channels impairment without the need to use high power at the transmitter.

Recently, a new concept that is being actively studied in multihop-augmented networks is multiuser cooperativediversity, where several terminals forma kind of coalition to assist each other with the transmission of their messages.

In general, cooperative relaying systems have a source node multicasting a message to a number of cooperative relays, which in turn resend a processed version to the intended destination node. The destination node combines the signal received from the relays, possibly also taking into account the source’s original signal.

Cooperative diversity exploits two fundamentals features of wireless medium: its broadcast nature and its ability to achieve diversity through independent channels.

There are three advantages from this:

(1) Diversity. This occurs because different paths are likely to fade independently. The impact of this is expected to be seen in the physical layer, in the design of a receiver that can exploit this diversity.

(2) Beamforming gain. The use of directed beams should improve the capacity on the individual wireless links.The gains may be particularly significant if space-time coding schemes are used.

(3) Interference mitigation. A protocol that takes advantage of the wireless channel and the antennas and receivers available could achieve a substantial gain in system throughput by optimizing the processing done inthe cooperative relays and in the scheduling of retransmissions by the relays so as to minimize mutual interference and facilitate information transmission by cooperation.

Source: Multiuser Cooperative Diversity forWireless Networks by George K. Karagiannidis, Chintha Tellambura, Sayandev Mukherjee and Abraham O. Fapojuwo, Volume 2006, Article ID 17202

There are 3 main types of co-operative diversity which are self-explanatory in the diagram above:

Decode and Forward

Simple and adaptable to channel condition (power allocation)

If detection in relay node unsuccessful => detrimental for detection in receiver (adaptive algorithm can fix the problem)

Receiver need CSI between source and relay for optimum decoding

Amplify and Forward

Achieve full diversity

Performance better than direct transmission and decode-and-forward

achieve the capacity when number of relays tend to infinity

Coded Cooperation

transmit incremental redundancy for partner

Automatic manage through code design

no feedback required between the source and relay

Rely on full decoding at the relay => cannot achieve full diversity!

Not scalable to large cooperating groups.