Sunday 10 April 2011

Cognitive radio – the way out of spectrum crunch?

Another presentation from the Cambridge Wireless Event on Avoiding Cellular Gridlock. One of the ways suggested in the discussions with regards to the 'Geo-location database' (see slide 12) is that they could also be done using Smart Grids. Though it sounds simple in theory, practically we may never see that happen and that would not be due to any technical reasons.

Wednesday 6 April 2011

Mobile Phone Antennas and Networks

We all remember the so called 'Antennagate' where the iPhone 4 loses coverage due to the way its held. As can be seen from the above picture, there are a lot of antennas already in the phones and yes they are on the increase with LTE and other technologies being added all the time.

Apple admitted the fault and claimed to have fixed the problem but its well known in technical circles that the fix is more of a software hack which doesn't really fix the problem just pretends to fix it. That is why the networks dread it and you can find awful lot of information on the web about the problems.

In a recent Cambridge Wireless event, I heard an interesting talk from Trevor Gill of Vodafone and one of the slides that caught my attention was the impact of these poorly designed phones on the network. The slide is embedded below.

It is estimated that the RF performance of iPhone4 is around 6dB worse than most other 3G phones. What this means is that you may be getting 4 bars of reception on your other phone where iPhone4 may be having only 1 or 2 bars or reception. So if the reception is poor with 1 or 2 bars, iPhone4 may have no reception at all.

To fix this problem, either the networks can increase the number of base stations to double the existing amount which is a huge cost to the networks and extra radiation or the phones can fix it themseles by having an extra antenna. In fact as the slide says, extra antenna on each phone would translate to increase in network capacity by 20-40%, cell area by 30% and cell edge throughput by 40-75%.

One final thing that I want to mention is that testing (RF, RRM, Conformance, etc.) are mandated by the networks for most phones but they overlook the testing procedure for phones like iPhone. What this means is that they do get a lot more new customers but they get new sets of problems. If these problems are not handled well, the impression they give is that the particular network is rubbish. Another thing is that the devices use a certain build/prototype for testing but the one that they release may contain other patches that can cause chaos. One such problem was Fast Dormancy problem that I have blogged about here.

Hopefully the networks will be a bit more careful and will put quality before quantity in future.

Monday 4 April 2011

Smart Grids: Beyond their remit

I blogged about the Smart Grid developments, nearly 2 years back here. Since then we have started talking about the 50 Billion connected M2M devices. Though Smart Grids as such can be just limited to distributing the electricity efficiently and dynamically, it has been said that they can be used for doing more than what they have been created for.

One such discussion in a recently concluded Cambridge Wireless Event on "Avoiding Cellular Gridlock: Finding New Ways Forward in Radio" was to use these smart grids for collecting the information about its surrounding.

It is well known that quite a few whitespace exist in radio communication in every country. We can build a cognitive radio that can use these whitespace and accordingly harness these free spectrum to the advantage of the users. Now since these whitespace would be different in each country and would also change depending on if a certain frequency is allocated in one area but not in another, there would need to be a database that the devices could use to find which spectrum is available or not.

Smart grids can be used to collect this information and update the database as they would have a wide footprint, probably encompassing the whole country. Though this is just an idea that came up in discussion, there could be more similar uses of smart grids.

For those of you who do not know much about smart grids, I have embedded couple of presentation from different chapters of The IET.





One thing worth mentioning is that, there is already a concern that Smart Grids could be an invasion of privacy and could also be exploited by highly skilled theives.

Picture Source: Washington Post

If you look at the picture above, an expert in smart grids could be able to point out the different signatures of power consumption match to a particular event related generally to a device. So for example of you have used a kettle that means you have not gone on holidays, or something like that.

This also gives opportunity for new devices that can randomize these signatures :)

Wednesday 30 March 2011

Quick Recap of MIMO in LTE and LTE-Advanced

I had earlier put up some MIMO presentations that were too technical heavy so this one is less heavy and more figures.

The following is from NTT Docomo Technical journal (with my edits):

MIMO: A signal transmission technology that uses multiple antennas at both the transmitter and receiver to perform spatial multiplexing and improve communication quality and spectral efficiency.

Spectral efficiency: The number of data bits that can be transmitted per unit time and unit frequency band.

In this blog we will first look at MIMO in LTE (Release 8/9) and then in LTE-Advanced (Release-10)

MIMO IN LTE

Downlink MIMO Technology

Single-User MIMO (SU-MIMO) was used for the downlink for LTE Rel. 8 to increase the peak data rate. The target data rates of over 100 Mbit/s were achieved by using a 20 MHz transmission bandwidth, 2 × 2 MIMO, and 64 Quadrature Amplitude Modulation (64QAM), and peak data rates of over 300 Mbit/s can be achieved using 4×4 SU-MIMO. The multi-antenna technology used for the downlink in LTE Rel. 8 is classified into the following three types.

1) Closed-loop SU-MIMO and Transmit Diversity: For closed-loop SU-MIMO transmission on the downlink, precoding is applied to the data carried on the Physical Downlink Shared Channel (PDSCH) in order to increase the received Signal to Interference plus Noise power Ratio (SINR). This is done by setting different transmit antenna weights for each transmission layer (stream) using channel information fed back from the UE. The ideal transmit antenna weights for precoding are generated from eigenvector(s) of the covariance matrix of the channel matrix, H, given by HHH, where H denotes the Hermitian transpose.

However, methods which directly feed back estimated channel state information or precoding weights without quantization are not practical in terms of the required control signaling overhead. Thus, LTE Rel. 8 uses codebook-based precoding, in which the best precoding weights among a set of predetermined precoding matrix candidates (a codebook) is selected to maximize the total throughput on all layers after precoding, and the index of this matrix (the Precoding Matrix Indicator (PMI)) is fed back to the base station (eNode B) (Figure 1).


LTE Rel. 8 adopts frequency-selective precoding, in which precoding weights are selected independently for each sub-band of bandwidth from 360 kHz to 1.44 MHz, as well as wideband precoding, with single precoding weights that are applied to the whole transmission band. The channel estimation used for demodulation and selection of the precoding weight matrix on the UE is done using a cell specific Reference Signal (RS) transmitted from each antenna. Accordingly, the specifications require the eNode B to notify the UE of the precoding weight information used for PDSCH transmission through the Physical Downlink Control Channel (PDCCH), and the UE to use this information for demodulation.

LTE Rel. 8 also adopts rank adaptation, which adaptively controls the number of transmission layers (the rank) according to channel conditions, such as the received SINR and fading correlation between antennas (Figure 2). Each UE feeds back a Channel Quality Indicator (CQI), a Rank Indicator (RI) specifying the optimal rank, and the PMI described earlier, and the eNode B adaptively controls the number of layers transmitted to each UE based on this information.

2) Open-loop SU-MIMO and Transmit Diversity: Precoding with closed-loop control is effective in low mobility environments, but control delay results in less accurate channel tracking ability in high mobility environments. The use of open-loop MIMO transmission for the PDSCH, without requiring feedback of channel information, is effective in such cases. Rank adaptation is used, as in the case of closed-loop MIMO, but rank-one transmission corresponds to open-loop transmit diversity. Specifically, Space-Frequency Block Code (SFBC) is used with two transmit antennas, and a combination of SFBC and Frequency Switched Transmit Diversity (FSTD) (hereinafter referred to as “SFBC+FSTD”) is used with four transmit antennas. This is because, compared to other transmit diversity schemes such as Cyclic Delay Diversity (CDD), SFBC and SFBC+FSTD achieve higher diversity gain, irrespective of fading correlation between antennas, and achieve the lowest required received SINR. On the other hand, for PDSCH transmission with rank of two or higher, fixed precoding is used regardless of channel variations. In this case, cyclic shift is performed before applying the precoding weights, which effectively switches precoding weights in the frequency domain, thereby averaging the received SINR is over layers.

3) Adaptive Beamforming: Adaptive beamforming uses antenna elements with a narrow antenna spacing of about half the carrier wavelength and it has been studied for use with base stations with the antennas mounted in a high location. In this case beamforming is performed by exploiting the UE Direction of Arrival (DoA) or the channel covariance matrix estimated from the uplink, and the resulting transmit weights are not selected from a codebook. In LTE Rel. 8, a UE-specific RS is defined for channel estimation in order to support adaptive beamforming. Unlike the cell-specific RS, the UE specific RS is weighted with the same weights as the data signals sent to each UE, and hence there is no need to notify the UE of the precoding weights applied at the eNode B for demodulation at the UE. However, its effectiveness is limited in LTE Rel. 8 because only one layer per cell is supported, and it is an optional UE feature for Frequency Division Duplex (FDD).

Uplink MIMO Technology

On the uplink in LTE Rel. 8, only one-layer transmission was adopted in order to simplify the transmitter circuit configuration and reduce power consumption on the UE. This was done because the LTE Rel. 8 target peak data rate of 50 Mbit/s or more could be achieved by using a 20 MHz transmission bandwidth and 64QAM and without using SU-MIMO. However, Multi-User MIMO (MU-MIMO) can be used to increase system capacity on the LTE Rel. 8 uplink, using multiple receiver antennas on the eNode B. Specifically, the specification requires orthogonalization of the demodulation RSs from multiple UEs by assigning different cyclic shifts of a Constant Amplitude Zero Auto-Correlation (CAZAC) sequence to the demodulation RSs, so that user signals can be reliably separated at the eNode B. Demodulation RSs are used for channel estimation for the user-signal separation process.


MIMO TECHNOLOGY IN LTE-ADVANCED

Downlink 8-Layer SU-MIMO Technology

The target peak spectral efficiency in LTE-Advanced is 30 bit/s/Hz. To achieve this, high-order SU-MIMO with more antennas is necessary. Accordingly, it was agreed to extend the number of layers of SU-MIMO transmission in the LTE-Advanced downlink to a maximum of 8 layers. The number of transmission layers is selected by rank adaptation. The most significant issue with the radio interface in supporting up to 8 layers is the RS structure used for CQI measurements and PDSCH demodulation.

1) Channel State Information (CSI)-RS: For CQI measurements with up-to-8 antennas, new CSI-RSs are specified in addition to cell-specific RS defined in LTE Rel. 8 for up-to-four antennas. However, in order to maintain backward compatibility with LTE Rel. 8 in LTE-Advanced, LTE Rel. 8 UE must be supported in the same band as in that for LTE-Advanced. Therefore, in LTE Advanced, interference to the PDSCH of LTE Rel. 8 UE caused by supporting CSI-RS must be minimized. To achieve this, the CSI-RS are multiplexed over a longer period compared to the cell-specific RS, once every several subframes (Figure 3). This is because the channel estimation accuracy for CQI measurement is low compared to that for demodulation, and the required accuracy can be obtained as long as the CSIRS is sent about once per feedback cycle. A further reason for this is that LTE-Advanced, which offers higher data-rate services, will be developed to complement LTE Rel. 8, and is expected to be adopted mainly in low-mobility environments.


2) UE-specific RS: To allow demodulation of eight-layer SU-MIMO, the UE-specific RS were extended for SU-MIMO transmission, using a hybrid of Code Division Multiplexing (CDM) and Frequency Division Multiplexing (FDM) (Figure 4). The UE-specific RS pattern for each rank (number of layers) is shown in Figure 5. The configuration of the UE-specific RS in LTE-Advanced has also been optimized differently from those of LTE Rel.8, extending it for SU-MIMO as well as adaptive beamforming, such as by applying twodimensional time-frequency orthogonal CDM to the multiplexing between transmission layers.


Downlink MU-MIMO Technology

In addition to the peak data rate, the system capacity and cell-edge user throughput must also be increased in LTE-Advanced compared to LTE Rel. 8. MU-MIMO is an important technology for satisfying these requirements. With MU-MIMO and CoMP transmission (described earlier), various sophisticated signal processing techniques are applied at the eNode B to reduce the interference between transmission layers, including adaptive beam transmission (zero-forcing, block diagonalization, etc.), adaptive transmission power control and simultaneous multi-cell transmission. When these sophisticated transmission techniques are applied, the eNode B multiplexes the UE-specific RS described above with the PDSCH, allowing the UE to demodulate the PDSCH without using information about transmission technology applied by the eNode B. This increases flexibility in applying sophisticated transmission techniques on the downlink. On the other hand, PMI/CQI/RI feedback extensions are needed to apply these sophisticated transmission techniques, and this is currently being discussed actively at the 3GPP.

Uplink SU-MIMO Technology

To reduce the difference in peak data rates achievable on the uplink and downlink for LTE Rel. 8, a high target peak spectral efficiency of 15 bit/s/Hz was specified for the LTE-Advanced uplink. To achieve this, support for SU-MIMO with up to four transmission antennas was agreed upon. In particular, the two-transmission-antenna SU-MIMO function is required to satisfy the peak spectral efficiency requirements of IMT-Advanced.

For the Physical Uplink Shared Channel (PUSCH), it was agreed to apply SU-MIMO with closed-loop control using multiple antennas on the UE, as well as codebook-based precoding and rank adaptation, as used on the downlink. The eNode B selects the precoding weight from a codebook to maximize achievable performance (e.g., received SINR or user throughput after precoding) based on the sounding RS, which is used for measuring the quality of the channel transmitted by the UE. The eNode B notifies the UE of the selected precoding weight together with the resource allocation information used by the PDCCH. The precoding for rank one contributes to antenna gain, which is effective in increasing cell edge user throughput. However, considering control-information overhead and increases in Peak-to-Average Power Ratio (PAPR), frequency-selective precoding is not very effective in increasing system throughput, so only wideband precoding has been adopted.

Also, for rank two or higher, when four transmission antennas are used, the codebook has been designed not to increase the PAPR. The demodulation RS, which is used for channel estimation, is weighted with the same precoding weight as is used for the user data signal transmission. Basically, orthogonalization is achieved by applying a different cyclic shift to each layer, but orthogonalizing the code region using block spread together with this method is adopted.


Uplink Transmit Diversity Technology

Closed-loop transmit diversity is applied to PUSCH as described above for SU-MIMO. Application of transmit diversity to the Physical Uplink Control Channel (PUCCH) is also being studied. For sending retransmission request Acknowledgment (ACK) and Negative ACK (NAK) signals as well as scheduling request signals, application of Spatial Orthogonal-Resource Transmit Diversity (SORTD) using differing resource blocks per antenna or an orthogonalizing code sequence (cyclic shift, block spread sequence) has been agreed upon (Figure 6). However, with LTE-Advanced, the cell design must be done so that LTE Rel. 8 UE get the required quality at cell-edges, so applying transmit diversity to the control channels cannot contribute to increasing the coverage area, but only to reducing the transmission power required.

Monday 28 March 2011

Friday 25 March 2011

3GPP – DVB Workshop for Next generation Mobile TV standards

TSG RAN and TSG CT hosted a joint workshop with DVB project on commonalities between DVB-NGH and eMBMS

The workshop was opened by the RAN Chairman Mr. Takehiro Nakamura on Wednesday 16th March 11:07. This is the joint session between TSG RAN, TSG CT and DVB project expert. TSG CT Chairman Mr. Hannu Hietalahti reminded that the workshop can't make any formal decisions that would be binding on either 3GPP side or DVB project side. Any agreement needs to be confirmed in DVB project and 3GPP separately. From 3GPP side this needs to be done by 3GPP TSG RAN and 3GPP TSG CT meetings during this week. The goal of the workshop is to find a common agreement how to proceed the future work on DVB-NGH and eMBMS convergence and decide the best way forward. The joint session is expected to make recommendations to TSG SA #51 based on the service requirements for DVB-NGH and the commonalities with eMBMS that can be identified. TSG SA #51 will decide the best way forward on 3GPP side.

The MBMS presentation was embedded in this post. The DVB presentation is embedded below:



The minutes of the meeting are available here: http://3gpp.org/ftp/tsg_sa/TSG_SA/TSGS_51/Docs/SP-110185.zip

All the documents from this workshop are available here: http://www.3gpp.org/ftp/workshop/2011-03-16_RAN-CT-DVB/

It was agreed that for any 3GPP work the normal 3GPP working procedures should be used. The supporting 3GPP member companies were requested to initiate Study items in the appropriate 3GPP working groups with the aim of sending them for approval during the next Plenary cycle.

It was noted that 3GPP Rel-11 stage 1 is going to be frozen in September 2011. It was seen 3GPP DVB-NGH can be a part of Rel-11 if there are interest in 3GPP community. The interesting companies are expected to contribute according to 3GPP working procedures.

Interesting M2M Video by ETSI

Machine-to Machine Communications - David Boswarthick (15/02/2011) from ETSI – World Class Standards on Vimeo.

ETSI M2M: Building the Internet of Things

Presented by: David Boswarthick, ETSI Technical Expert

Live Presentation during MWC 2011: ETSI stand, Monday, 15 February 2011

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About the presenter:

David Boswarthick, Technical Officer, ETSI

David has been extensively involved for over 10 years in the standardization activities of mobile, fixed and convergent networks in both the European Telecommunications Standards Institute (ETSI) and the 3rd Generation Partnership Project (3GPP). He is currently involved in the M2M standards group which is defining an end to end architecture and requirements for multiple M2M applications including Smart Metering, healthcare and enhanced home living. David holds a Bachelor's Honours Degree in Telecommunications from the University of Plymouth, and a Master's Degree in Networks and Distributed systems from the University of Nice and Sophia Antipolis, France.