LTE/LTE-A SON (for Femtocells)

LTE/LTE-A SON (for Femtocells)

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A Video presentation of the above is embedded below:



PDF of the above presentation is available here.

LTE Evolution - Soft Cell

LTE Evolution - CoMP

What is coming next after LTE and IMT-Advanced

Interesting presentation from NSN

What is coming next after LTE and IMT-Advanced

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Other related posts:

• Next Mobile Network (NMN)
• 4G Mobile Broadband Evolution: 3GPP Release-10 and Beyond

Donor eNB (DeNB) and Relay Node (RN)

Extracted from 3GPP 36.300:

The eNB hosts the following functions:

- Functions for Radio Resource Management: Radio Bearer Control, Radio Admission Control, Connection Mobility Control, Dynamic allocation of resources to UEs in both uplink and downlink (scheduling);

- IP header compression and encryption of user data stream;

- Selection of an MME at UE attachment when no routing to an MME can be determined from the information provided by the UE;

- Routing of User Plane data towards Serving Gateway;

- Scheduling and transmission of paging messages (originated from the MME);

- Scheduling and transmission of broadcast information (originated from the MME or O&M);

- Measurement and measurement reporting configuration for mobility and scheduling;

- Scheduling and transmission of PWS (which includes ETWS and CMAS) messages (originated from the MME);

- CSG handling;

- Transport level packet marking in the uplink.

The DeNB hosts the following functions in addition to the eNB functions:

- S1/X2 proxy functionality for supporting RNs;

- S11 termination and S-GW/P-GW functionality for supporting RNs.

E-UTRAN supports relaying by having a Relay Node (RN) wirelessly connect to an eNB serving the RN, called Donor eNB (DeNB), via a modified version of the E-UTRA radio interface, the modified version being called the Un interface. The RN supports the eNB functionality meaning it terminates the radio protocols of the E-UTRA radio interface, and the S1 and X2 interfaces. From a specification point of view, functionality defined for eNBs, e.g. RNL and TNL, also applies to RNs unless explicitly specified. RNs do not support NNSF. In addition to the eNB functionality, the RN also supports a subset of the UE functionality, e.g. physical layer, layer-2, RRC, and NAS functionality, in order to wirelessly connect to the DeNB.

The architecture for supporting RNs is shown in Figure 4.7.2-1. The RN terminates the S1, X2 and Un interfaces. The DeNB provides S1 and X2 proxy functionality between the RN and other network nodes (other eNBs, MMEs and S GWs). The S1 and X2 proxy functionality includes passing UE-dedicated S1 and X2 signalling messages as well as GTP data packets between the S1 and X2 interfaces associated with the RN and the S1 and X2 interfaces associated with other network nodes. Due to the proxy functionality, the DeNB appears as an MME (for S1-MME), an eNB (for X2) and an S-GW (for S1-U) to the RN.

For more details see - 3GPP TS 36.300 : Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall description; Stage 2 (Release 10)

LTE Advanced HetNet Benefits!

Presentation from Qualcomm Webinar, LTE-Advanced Hetnet benefits.

LTE Advanced HetNet Benefits!

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Qualcomm is undisputed leader in the LTE chipsets and have been pushing hard for the next generation LTE-A chipsets. Here is a promotional LTE-Advanced Video on Youtube:

MU-MIMO (and DIDO)

Late last month a guy called Steve Perlman announced of a new technology called DIDO (Distributed-Input-Distributed-Output) that could revolutionise the way wireless transmission works and can help fix the channel capacity problem as described by Shannon's formula. A whitepaper describing this technology is available here.

I havent gone through the paper in any detail nor do I understand this DIDO very well but what many experienced engineers have pointed out is that this is MU-MIMO in disguise. Without going into any controversies, lets look at MU-MIMO as its destined to play an important part in LTE-Advanced (the real '4G').

Also, I have been asked time and again about this Shannon's channel capacity formula. This formula is better known by its name Shannon-Hartley theorem. It states:

C <= B log2 (1 + S/N)

where:

C = channel capacity (bits per second)

B = bandwidth (hertz)

S/N = Signal to Noise ratio (SNR)

In a good channel, SNR will be high. Take for example a case when SNR is 20db then log2 (1 + 100) = 6.6. In an extremely noisy channel SNR will be low which would in turn reduce the channel capacity.

In should be pointed out that the Shannon's formula holds true for all wireless technologies except for when multiuser transmission like MU-MIMO (or DIDO) is used.

Anyway, I gave a simple explanation on MU-MIMO before. Another simple explanation of what an MU-MIMO is as explained in this video below:

The picture below (from NTT) gives a good summary of the different kinds of MIMO technology and their advantages and disadvantages. More details could be read from here.

Click to enlarge

As we can see, MU-MIMO is great but it is complex in implementation.

Click to enlarge

Multiuser MIMO technology makes it possible to raise wireless transmission speed by increasing the number of antennas at the base station, without consuming more frequency bandwidth or increasing modulation multiple-values. It is therefore a promising technology for incorporating broadband wireless transmission that will be seamlessly connected with wired transmission in the micro waveband (currently used for mobile phones and wireless LAN, and well suited to mobile communications use), where frequency resources are in danger of depletion. Since it also allows multiple users to be connected simultaneously, it is seen as a solution to the problem specific to wireless communications, namely, slow or unavailable connections when the number of terminals in the same area increases (see Figure 9 above).

There is a good whitepaper in NTT Docomo technical journal that talks about Precoding and Scheduling techniques for increasing the capacity of MIMO channels. Its available here. There is also a simple explanation of MIMO including MU-MIMO on RadioElectronics here. If you want to do a bit more indepth study of MU-MIMO then there is a very good research paper in the EURASIP Journal that is available here (Click on Full text PDF on right for FREE download).

Finally, there is a 3GPP study item on MIMO Enhancements for LTE-Advanced which is a Release-11 item that will hopefully be completed by next year. That report should give a lot more detail about how practical would it be to implement it as part of LTE-Advanced. The following is the justification of doing this study:

The Rel-8 MIMO and subsequent MIMO enhancements in Rel-10 were designed mostly with homogenous macro deployment in mind. Recently, the need to enhance performance also for non-uniform network deployments (e.g. heterogeneous deployment) has grown. It would therefore be beneficial to study and optimize the MIMO performance for non-uniform deployments where the channel conditions especially for low-power node deployments might typically differ from what is normally encountered in scenarios considered so far.

Downlink MIMO in LTE-Advanced has been enhanced in Release 10 to support 8-layer SU-MIMO transmission and dynamic SU-MU MIMO switching. For the 8-tx antenna case, the CSI feedback to support downlink MIMO has been enhanced with a new dual-codebook structure aimed at improving CSI accuracy at the eNB without increasing the feedback overhead excessively. Precoded reference symbols are provided for data demodulation, allowing arbitrary precoders to be used by the eNB for transmission. In many deployment scenarios, less than 8 tx antennas will be employed. It is important to focus on the eNB antenna configurations of highest priority for network operators.

The enhancement of MIMO performance through improved CSI feedback for high priority scenarios not directly targeted by the feedback enhancements in Release 10, especially the case of 4 tx antennas in a cross-polarised configuration, in both homogeneous and heterogeneous scenarios should be studied.

MU-MIMO operation is considered by many network operators as important to further enhance system capacity. It is therefore worth studying further potential enhancement for MU-MIMO, which includes UE CSI feedback enhancement and control signaling enhancement. Furthermore, open-loop MIMO enhancements were briefly mentioned but not thoroughly investigated in Rel-10.

In addition, the experience from real-life deployments in the field has increased significantly since Rel-8. It would be beneficial to discuss the experience from commercial MIMO deployments, and identify if there are any potential short-comings and possible ways to address those. For example, it can be discussed if robust rank adaptation works properly in practice with current UE procedures that allow a single subframe of data to determine the rank. In addition the impact of calibration error on the performance could be discussed.

This work will allow 3GPP to keep MIMO up to date with latest deployments and experience.

Benefits of Self Optimizing Networks in LTE

Self Optimizing Networks : Benefits of SON in LTE - July 2011

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Mobility Robustness Optimization to avoid Handover failures

The following is from 4G Americas Whitepaper on SON:

Mobility Robustness Optimization (MRO) encompasses the automated optimization of parameters affecting active mode and idle mode handovers to ensure good end-user quality and performance, while considering possible competing interactions with other SON features such as, automatic neighbor relation and load balancing.

There is also some potential for interaction with Cell Outage Compensation and Energy Savings as these could also potentially adjust the handover boundaries in a way that conflicts with MRO. While the goal of MRO is the same regardless of radio technology namely, the optimization of end-user performance and system capacity, the specific algorithms and parameters vary with technology.

The objective of MRO is to dynamically improve the network performance of HO (Handovers) in order to provide improved end-user experience as well as increased network capacity. This is done by automatically adapting cell parameters to adjust handover boundaries based on feedback of performance indicators. Typically, the objective is to eliminate Radio Link Failures and reduce unnecessary handovers. Automation of MRO minimizes human intervention in the network management and optimization tasks.

The scope of mobility robustness optimization as described here assumes a well-designed network with overlapping RF coverage of neighboring sites. The optimization of handover parameters by system operators typically involves either focused drive-testing, detailed system log collection and postprocessing, or a combination of these manual and intensive tasks. Incorrect HO parameter settings can negatively affect user experience and waste network resources by causing HO ping-pongs, HO failures and Radio Link Failures (RLF). While HO failures that do not lead to RLFs are often recoverable and invisible to the user, RLFs caused by incorrect HO parameter settings have a combined impact on user experience and network resources. Therefore, the main objective of mobility robustness optimization should be the reduction of the number of HO-related radio link failures. Additionally, sub-optimal configuration of HO parameters may lead to degradation of service performance, even if it does not result in RLFs. One example is the incorrect setting of HO hysteresis, which may results in ping-pongs or excessively delayed handovers to a target cell. Therefore, the secondary objective of MRO is the reduction of the inefficient use of network resources due to unnecessary or missed handovers.

Most problems associated with HO failures or sub-optimal system performance can ultimately be categorized, as either too-early or too-late triggering of the handover, provided that the required fundamental network RF coverage exists. Thus, poor HO-related performance can generally be categorized by the following events:

* Intra-RAT late HO triggering

* Intra-RAT early HO triggering

* Intra-RAT HO to an incorrect cell

* Inter-RAT too late HO

* Inter RAT unnecessary HO

Up to Release 9, a UE is required to send RLF report only in case of successful RRC re-establishment after a connection failure. Release 10 allows support for RLF reports to be sent even when the RRC reestablishment does not succeed. The UE is required to report additional information to assist the eNB in determining if the problem is coverage related (no strong neighbors) or handover problems (too early, too late or wrong cell). Furthermore, Release 10 allows for precise detection of too early / wrong cell HO.

Carrier Aggregation with a difference

Click on picture to enlarge

Another one from the LTE World Summit. This is from a presentation by Ariela Zeira of Interdigital.

What is being proposed is that Carrier Aggregation can use both the licensed as well as unlicensed bands but the signalling should only happen in the licensed band to keep the operator in control.

Note that this is only proposed for Small Cells / Femtocells.

The only concern that I have with this approach is that this may cause interference with the other devices using the same band (especially ISM band). So the WiFi may not work while the LTE device is aggregating this ISM band and the same goes for bluetooth.

Comments welcome!

New Security Algorithms in Release-11

Security in 3GPP

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I did mention in my earlier blog post about the new algorithm for 3GPP LTE-A Security. The good news is that this would be out hopefully in time for the Release-11.

The following from 3GPP Docs:

The current 3GPP specifications for LTE/SAE security support a flexible algorithm negotiation mechanism. There could be sixteen algorithms at most to support LTE/SAE confidentiality and integrity protection. In current phase, 3GPP defines that there are two algorithms used in EPS security, i.e. SNOW 3G and AES. The remaining values have been reserved for future use. So it is technically feasible for supporting new algorithm for LTE/SAE ciphering and integrity protection.

Different nations will have different policies for algorithm usage of communication system. The current defined EPS algorithm may not be used in some nations according to strict policies which depend on nation’s security laws. Meanwhile, operators shall implement their networks depending on national communication policies. To introduce a new algorithm for EPS security will give operators more alternatives to decide in order to obey national requirements.

Picture: Zu Chongzi

Picture Source: Wikipedia

Some work has been done to adapt LTE security to national requirements about cryptography of LTE/SAE system, i.e. designing a new algorithm of EPS security, which is named ZUC (i.e. Zu Chongzhi, a famous Chinese scientist name in history). Certainly the new algorithm should be fundamentally different from SNOW 3G and AES, so that an attack on one algorithm is very unlikely to translate into an attack on the other.

The objective of this work item is to standardise a new algorithm in EPS. This will include the following tasks:

• To develop new algorithms for confidentiality and integrity protection for E-UTRAN

• To enable operators to quickly start to support the new algorithm

• Not to introduce any obstacle for R8 roaming UE

The following issues should at least be handled in the WI:

• Agree requirement specification with ETSI SAGE for development of new algorithms

• Delivery of algorithm specification, test data and design and evaluation reports

The algorithm is provided for 3GPP usage on royalty-free basis.

The algorithm shall undergo a sequential three-stage evaluation process involving first ETSI SAGE, then selected teams of cryptanalysts from academia and finally the general public.

The documents related to the EEA3 and EIA3 algorithm could be downloaded from here.

If you are new to LTE Security, the following can be used as starting point: http://www.3g4g.co.uk/Lte/LTE_Security_WP_0907_Agilent.pdf

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.

Qualcomm Video on LTE Advanced: Heterogeneous Networks

RAN mechanisms to avoid CN overload due to MTC

Machine-to-Machine (M2M) is the future and Machine-type communications (MTC) will be very important once we have billions of connected devices. I have talked in the past about the 50 Billion connected devices by 2050 and the Internet of Things.

One of the challenges of today's networks is to handle this additional signalling traffic due to MTC. One of the very important topics being discussed in 3GPP RAN meetings is 'RAN mechanisms to avoid CN overload due to MTC'. Even though it has not been finalised, its interesting to see the direction in which things are moving.

The above figure from R2-106188 shows that an extended wait time could be added in the RRC Connection Reject/Release message in case if the eNodeB is overloaded. The device can reattempt the connection once the wait time has expired.

In R2-110462, another approach is shown where Core Network (CN) is overloaded. Here a NAS Request message is sent with delay tolerant indicator a.k.a. low priority indicator. If the CN is overloaded then it can reject the request with a backoff timer. Another approach would be to send this info to the eNodeB that can do a RRC Connection Reject when new connection request is received.

All Documents from 3GPP RAN2 #72-bis are available here. Search for NIMTC for M2M related and overload related docs.

SI on Signalling and procedure for interference avoidance for in-device coexistence

In order to allow users to access various networks and services ubiquitously, an increasing number of UEs are equipped with multiple radio transceivers. For example, a UE may be equipped with LTE, WiFi, and Bluetooth transceivers, and GNSS receivers. One resulting challenge lies in trying to avoid coexistence interference between those collocated radio transceivers. Figure 4-1 below shows an example of coexistence interference.

3GPP initiated a Study Item (SI) in Release-10 timeframe to investigate the effects of the interference due to multiple radios and signalling. This study is detailed in 3GPP TR 36.816 (see link at the end).

Due to extreme proximity of multiple radio transceivers within the same UE, the transmit power of one transmitter may be much higher than the received power level of another receiver. By means of filter technologies and sufficient frequency separation, the transmit signal may not result in significant interference. But for some coexistence scenarios, e.g. different radio technologies within the same UE operating on adjacent frequencies, current state-of-the-art filter technology might not provide sufficient rejection. Therefore, solving the interference problem by single generic RF design may not always be possible and alternative methods needs to be considered. An illustration of such kind of problem is shown in Figure 4-2 above.

The following scenarios were studied:

- LTE coexisting with WiFi

- LTE coexisting with Bluetooth

- LTE Coexisting with GNSS

Based on the analysis in SI, some examples of the problematic coexistence scenarios that need to be further studied are as follows:

- Case 1: LTE Band 40 radio Tx causing interference to ISM radio Rx;

- Case 2: ISM radio Tx causing interference to LTE Band 40 radio Rx;

- Case 3: LTE Band 7 radio Tx causing interference to ISM radio Rx;

- Case 4: LTE Band 7/13/14 radio Tx causing interference to GNSS radio Rx.

In order to facilitate the study, it is also important to identify the usage scenarios that need to be considered. This is because different usage scenarios will lead to different assumption on behaviours of LTE and other technologies radio, which in turn impact on the potential solutions. The following scenarios will be considered:

1a) LTE + BT earphone (VoIP service)

1b) LTE + BT earphone (Multimedia service)

2) LTE + WiFi portable router

3) LTE + WiFi offload

4) LTE + GNSS Receiver

The SI also proposes some ways of reducing the interference and is work in progress at the moment.

Reference: 3GPP TR 36.816 : Study on signalling and procedure for interference avoidance for in-device coexistence; (Release 10).

LTE-Advanced (Rel-10) UE Categories

I blogged about the 1200Mbps of DL with LTE Advanced earlier and quite a few people asked me about the bandwidth, etc. I found another UE categories table in Agilent lterature on LTE-Advanced here.

The existing UE categories 1-5 for Release 8 and Release 9 are shown in Table 4. In order to accommodate LTE-Advanced capabilities, three new UE categories 6-8 have been defined.

Note that category 8 exceeds the requirements of IMT-Advanced by a considerable

margin.

Given the many possible combinations of layers and carrier aggregation, many configurations could be used to meet the data rates in Table 4. Tables 5 and 6 define the most probable cases for which performance requirements will be developed.

eICIC: Enhanced inter-cell interference coordination in 3GPP Release-10

Inter-cell interference coordination (ICIC) was introduced in Release-8/9 of the 3GPP LTE standards. The basic idea of ICIC is keeping the inter-cell interferences under control by radio resource management (RRM) methods. ICIC is inherently a multi-cell RRM function that needs to take into account information (e.g. the resource usage status and traffic load situation) from multiple cells.

Broadly speaking, the main target of any ICIC strategy is to determine the resources (bandwidth and power) available at each cell at any time. Then (and typically), an autonomous scheduler assigns those resources to users. Thus, from the Radio Resource Control perspective, there are two kind of decisions: (a) which resources will be allocated to each cell? and, (b) which resources will be allocated to each user?. Clearly, the temporality of such decisions is quite different. Whereas resources to users allocation is in the order of milliseconds, the allocation of resources to cells take much longer periods of time or can be fixed.

Static ICIC schemes are attractive for operators since the complexity of their deployment is very low and there is not need for new extra signaling out of the standard. Static ICIC mostly relies on the fractional reuse concept. This means that users are categorized according to their Signal-to-Noise-plus-Interference Ratio (SINR), that means basically according to their inter-cell interference, and different reuse factors are applied to them, being higher at regions with more interference, mostly outer regions of the cells. The total system bandwidth is divided into sub-bands which are used by the scheduler accordingly.

A simple way to explain ICIC is based on picture above. The users are divided into two categories, one is Cell Center User (CCU), and the other one is Cell Edge User (CEU). CCUs are the users distributed in the gray region of above figure, and CEUs are the users distributed in the above red, green and blue areas. CCU can use all the frequencypoints to communicate with the base station, while CEU must use corresponding specified frequency points to ensure orthogonality between different cells.

CEUs can be assigned a higher transmissionpower for the frequency reuse factor is greater than 1. The frequency points are not overlapped at the edges so the adjacent cell interference is small. CCU’s frequency reuse factor is 1; for the path loss is small and transmission power is low. Therefore the interference to the adjacent cells is not high either.

Dominant interference condition has been shown when Non-CSG/CSG users are in close proximity of Femto, in this case, Rel8/9 ICIC techniques are not fully effective in mitigating control channel interference, and hence, Enhanced interference management is needed At least the following issues should be addressed by any proposed solutions:

o Radio link monitoring (RLM)

o Radio Resource Management (including detection of PSS/SSS and PBCH)

o Interference from CRS

oo To PCFICH/PHICH/PDCCH

oo To PDSCH

o CSI measurement

o Interference from PDCCH masked with P-RNTI and SI-RNTI (for SIB-1 only) and associated PCFICH

As a result, from Release-10 onwards eICIC work was started. In Rel-10, two eICIC or Enhanced inter-cell interference coordination (also incorrectly referred to as Enhanced Inter-Cell Interference Cancellation) were being actively discussed. They are Time domain eICIC and autonomous HeNB power setting. More advanced ideas are being thought of beyong Rel-10 including Interference management techniques on carrier resolution ( optimally exploiting available Networks frequency assets (carriers in same or different bands) , combination with Carrier Aggregation; interference management schemes proposed both during LTE-Advanced Study Item phase, and during Rel-10 HetNet eICIC work.

From an earlier presentation in SON Conference:

eICIC:

- Effectively extends ICIC to DL control - time domain

- Requires synchronization at least between macro eNB and low power eNBs in its footprint

- No negative impact on legacy Rel 8 Use

Range Extension(RE)

- Refers to UE ability to connect and stay connected to a cell with low SINR

- Achieved with advanced UE receivers - DL interference cancellation (IC)

RE + eICIC technique:

– Eliminates coverage holes created by closed HeNBs

– Improves load balancing potential for macro network with low power eNBs and leads to significant network throughput increase

–Enables more UEs can be served by low power eNBs, which can lead to substantially higher network throughput

More details on eICIC is available in 3GPP CR's and TR's listed below:

• R1-105081: Summary of the description of candidate eICIC solutions, 3GPP TSG-WG1 #62, Madrid, Spain, August 23rd – 27th, 2010.
• R1-104942: Views on eICIC Schemes for Rel-10, 3GPP TSG RAN WG1 Meeting #62, Madrid, Spain, 23-27 August, 2010.
• R1-104238: eICIC Chairman’s note, 3GPP TSG RAN WG1 Meeting #61bis, Dresden, Germany, 28th June – 2nd July 2010.
• R1-103822: Enhanced ICIC considerations for HetNet scenarios, 3GPP TSG RAN WG1 #61bis Meeting, Dresden, Germany, June 28 – July 2, 2010.

You can also check out NTT Docomo's presentation on LTE Enhancements and Future Radio Access here.

An Intellectual Property Rights Primer

Page 5-8 is a very good starting point to understand the IPR issues surrounding LTE.

The Essentials of Intellectual Property - Sep 2010

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An accompanying video and download information is available on Ericsson's website here.

What are Heterogeneous Networks (HetNets)?

HetNets are hot. I hear about them in various contexts. Its difficult to find exactly what they are and how they will work though. There is a HetNets special issue in IEEE Communications Magazine coming out next year but that's far away.

I found an interesting summary on HetNets in Motorola Ezine that is reproduced below:

“The bigger the cell site, the less capacity per person you have,” said Peter Jarich, research director with market intelligence firm Current Analysis. “If you shrink coverage to a couple of blocks, you are having that capacity shared with a fewer number of people, resulting in higher capacity and faster data speeds.”

This is a topic the international standards body, the Third Generation Partnership Project (3GPP), has been focusing on to make small cells part of the overall cellular network architecture.

“What we’re seeing is a natural progression of how the industry is going to be addressing some of these capacity concerns,” said Joe Pedziwiatr, network systems architect with Motorola. “There is a need to address the next step of capacity and coverage by introducing and embracing the concepts of small cells and even looking at further advances such as better use of the spectrum itself.”

As such, discussion regarding this small-cell concept has emerged into what is called heterogeneous networks, or Het-Net, for short. The idea is to have a macro wireless network cooperating with intelligent pico cells deployed by operators to work together within the macro network and significantly improve coverage and augment overall network capacity. Small cells can also be leveraged to improve coverage and deliver capacity inside buildings. Indoor coverage has long been the bane of mobile operators. Some mobile operators are already leveraging this concept, augmenting their cellular service offering with WiFi access to their subscriber base in order to address the in-building coverage and capacity challenges facing today’s cellular solutions.

Pedziwiatr said this Het-Net structure goes far beyond what is envisioned for femtocells or standard pico cells for that matter. Introducing a pico cell into the macro network will address but just one aspect of network congestion, namely air interface congestion. The backhaul transport network may become the next bottleneck. Finally, if all this traffic hits the core network, the congestion will just have shifted from the edge to the core.

“This requires a system focus across all aspects of planning and engineering,” Pedziwiatr said. “We’re trying to say it goes beyond that of a femto. If someone shows up at an operator and presents a pico cell, that is just one percent of what would be needed to provide true capacity relief for the macro network.”

Femtocells, otherwise known as miniature take-home base stations, are obtained by end users and plugged into a home or office broadband connection to boost network signals inside buildings. A handful of 3G operators worldwide are selling femtocells as a network coverage play. For the LTE market, the Femtocell Forum is working to convince operators of the value of a femtocell when it comes to better signal penetration inside buildings and delivering high-bandwidth services without loading the mobile network. This is possible, because the backhaul traffic runs over the fixed line connection. However, this femtocell proposition largely relies on end user uptake of them—not necessarily where operators need them, unless they install femtocells themselves or give end users incentives to acquire them.

As with any new concept, there are challenges to overcome before Het-Nets can become reality. Het-Nets must come to market with a total cost of ownership that is competitive for an operator to realize the benefit of providing better capacity, higher data speeds, and most of all, a better end-user experience said Chevli.

“The level of total cost of ownership has to be reduced. That is where the challenge is for vendors to ensure that any new solution revalidates every existing tenet of cellular topology and evolve it to the new paradigm being proposed,” Chevli said. “You can’t increase the number of end nodes by 25X and expect to operate or manage this new network with legacy O&M paradigms and a legacy backhaul approach.”

One of the issues is dealing with interference and Het-Net network traffic policies. “How do you manage all of these small cell networks within the macrocell network?” asked Jarich. “Right now if you have a bunch of femtocells inside a house, there is this concept that the walls stop the macrocell signals from getting in and out. You get a separation between the two. Go outdoors with small cells underlying bigger cells and you get a lot more interference and hand-off issues because devices will switch back and forth based on where the stronger signal is.”

Pedziwiatr said for a Het-Net to work, it would require a change in node management, whereby an operator isn’t burdened with managing big clusters of small cells on an individual basis. “We see elements of SON (self organizing networks), self discovery and auto optimization that will have to be key ingredients in these networks. Otherwise operators can’t manage them and the business case will be a lot less attractive,” he said.

Fortunately, the industry has already been working with and implementing concepts of SON in LTE network solutions. In the femtocell arena also, vendors have been incorporating some elements and concepts of SON so that installing them is a plug-and-play action that automatically configures the device and avoids interference. But even then, Het-Nets will require further SON enhancement to deal with new use cases, such as overlay (macro deployment) to underlay (pico deployments) mobility optimization.

When it comes to LTE, SON features are built into the standard, and are designed to offer the dual benefit of reducing operating costs while optimizing performance. SONs will do this by automating many of the manual processes used when deploying a network to reduce costs and help operators commercialize their new services faster. SON will also automate many routine, repetitive tasks involved in day-to-day network operations and management such as neighbor list discovery and management.

Other key sticking points are deployment and backhaul costs. If operators are to deploy many small cells in a given area, deploying them and backhauling their traffic should not become monumental tasks.

Chevli and Pedziwiatr envision Het-Nets being deployed initially in hot zone areas – where data traffic is the highest – using street-level plug-and-play nodes that can be easily installed by people with little technical know-how.

“Today, macro site selection, engineering, propagation analysis, rollout and optimization are long and expensive processes, which must change so that installers keep inventories of these units in their trucks, making rollout simple installations and power-ups,” said Pedziwiatr. “These will be maintained at a minimum with quick optimization.”

The notion of backhauling traffic coming from a large cluster of Het-Net nodes could also stymie Het-Nets altogether. Chevli said that in order to keep costs down, Het-Net backhaul needs to be a mix of cost-effective wireless or wired backhaul technology to aggregate traffic from what likely will be nodes sitting on lamp posts, walls, in-building and other similar structures. The goal then is to find a backhaul point of presence to aggregate the traffic and then put that traffic on an open transport network in the area.

Backhaul cost reductions may also be a matter of finding ways to reduce the amount of backhaul forwarded to the core network, Pedziwiatr said. These types of solutions are already being developed in the 3G world to cope with the massive data traffic that is beginning to crush networks. For traffic such as Internet traffic, which doesn’t need to travel through an operator’s core network, offloading that traffic as close to the source as possible would further drive down the cost of operation through the reduction of backhaul and capacity needs of the core network.

In the end, with operators incorporating smaller cells as an underlay to their macro network layer rather than relying on data offloading techniques such as femtocells and WiFi that largely depend on the actions of subscribers and impacted by the surrounding cell operating in the same unlicensed frequency, Het-Nets in licensed spectrum will soon become the keystone in attacking the ever-present congestion issue that widely plagues big cities and this is only likely to get worse over time.

Image Source: Dr. Daichi Imamura, Panasonic presentation.

Presentation: Further Enhancements for LTE-Advanced

Further Enhancements for LTE-Advanced

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