Multi-antenna techniques can significantly increase the data rates and reliability of a wireless communication system. The performance is in particular improved if both the transmitter and the receiver are equipped with multiple antennas, which results in a multiple-input multiple-output, “MIMO”, communication channel. Such systems and/or related techniques are commonly referred to as MIMO.
The LTE standard is currently evolving with enhanced MIMO support. A core component in LTE is the support of MIMO antenna deployments and MIMO related techniques. For instance, LTE-Advanced supports a spatial multiplexing mode that provides for channel-dependent precoding. The spatial multiplexing mode is intended for high data rates in favorable channel conditions and it relies on antenna precoding, which, as noted, may be channel dependent. This is also commonly referred to as closed-loop precoding, where the aim is to focus the transmit energy into a subspace that is strong in the sense of conveying much of the transmitted energy to the targeted user equipment or “UE”. In addition, the precoder matrix—which comprises the per antenna signal weightings—also may be selected to strive for orthogonalizing the channel, meaning that after proper linear equalization at the UE, the inter-layer interference is reduced.
Channel State Information Reference Symbols, “CSI-RS”, were introduced in LTE Release-10, for use in estimating channel state information or “CSI”. A CSI-RS resource can loosely be described as the pattern of resource elements on which a particular CSI-RS configuration is transmitted. A CSI-RS resource is determined by a combination of “resourceConfig”, “subframeConfig”, and “antennaPortsCount” parameters, which are configured by Radio Resource Control, “RRC”, signaling.
The CSI-RS provide several advantages over basing the CSI feedback on common reference symbols, “CRS”, which were used for CSI estimation in previous releases. First, the CSI-RS are not used for data signal demodulation, and thus do not require the same density—i.e., the overhead of the CSI-RS is substantially less than the CRS. Second, the CSI-RS provide a much more flexible basis for configuring CSI feedback measurements from UEs—e.g., which CSI-RS resource(s) to measure on can be configured in a UE specific manner. Moreover, supporting antenna configurations larger than four antennas must resort to the use of CSI-RS, because the CRS are only defined for a maximum of four antennas.
By measuring on a CSI-RS, a UE can estimate the effective channel the CSI-RS is traversing, including the radio propagation channel, antenna gains, and any possible antenna virtualizations—i.e., a CSI-RS port may be precoded so that it is virtualized over multiple physical antenna ports. In other words, the CSI-RS port can be transmitted on multiple physical antenna ports, possibly with different gains and phases. In more mathematical rigor this implies that if a known CSI-RS signal xn is transmitted, a UE can estimate the coupling between the transmitted signal and the received signal—i.e., the effective channel.
Hence if no virtualization is performed in the transmission of xn, the received signal yn can be expressed asyn=Hnxn+en,and the UE can estimate the effective channel Heff=Hn. Similarly, if the CSI-RS is virtualized using a transmit precoder matrix WNT×r asyn=HnWNT×rxn+en,then the UE can estimate the effective channel Heff=HnWNT×r, where NT=the number of transmit antennas used for precoding and r=the rank, i.e., the number of spatial multiplexing layers used.
The concept of zero-power CSI-RS resources—also known as a muted CSI-RS—is related to CSI-RS. Zero power CSI-RS resources are configured just as regular CSI-RS resources, so that a UE knows that data transmissions are mapped around those resources. However, the intent of the zero-power CSI-RS resources is to enable the network to mute transmissions on the corresponding resources, to thereby boost the signal-to-noise-plus-interference, “SINR”, of a corresponding non-zero power CSI-RS that is possibly transmitted in a neighbor cell/transmission point.
Release 11 of LTE introduces a special zero-power CSI-RS, for which a UE may be mandated to use in measuring interference plus noise. The UE can assume that the transmission points or “TPs” of interest are not transmitting on the zero-power CSI-RS resources, and the received power at the UE can therefore be used as a measure of the interference plus noise.
Based on a specified CSI-RS resource and on an interference measurement configuration—e.g. a zero-power CSI-RS resource—the UE can estimate the effective channel and noise plus interference, and consequently also determine which rank, precoder and transport format to recommend as best matching the particular channel.
For CSI feedback, LTE has adopted an implicit CSI mechanism in which a UE does not explicitly report the complex valued elements of a measured effective channel, for example. Instead, the UE recommends a transmission configuration for the measured effective channel. The recommended transmission configuration thus implicitly gives the network information about the underlying channel state.
In LTE, such CSI feedback is given in terms of a transmission rank indicator or “RI”, a precoder matrix indicator or “PMI”, and one or more channel quality indicators or “CQIs”. The CQI/RI/PMI report from a UE can be wideband or frequency-selective, depending on the configured reporting mode.
The RI corresponds to a recommended number of data streams that are to be spatially multiplexed and thus transmitted in parallel over the effective channel. The PMI identifies a recommended precoder, e.g., an index pointing to precoder matrix WNT×r in a codebook, to use for precoding the transmission. The PMI thus relates to the spatial characteristics of the effective channel. The CQI represents a recommended transport block size—i.e., the code rate. There is thus a relation between the CQI and the SINR of the spatial stream(s) over which the transport block is transmitted.
Coordinated Multipoint or “CoMP” transmission and reception refers to a system where the transmission and/or reception at multiple, geographically separated antenna sites is coordinated in order to improve system performance. More specifically, CoMP refers to coordination of antenna arrays that have different geographical coverage areas. An antenna covering a certain geographical area as a point is referred to herein as a “transmission point” or “TP”. Coordination among a set of CoMP TPs can be based on distributed or centralized control.
LTE uses CoMP to improve high data rate coverage, cell-edge throughput and/or to increase system throughput. In particular, the goal is to distribute the user-perceived system performance more evenly in the network by taking control of the interference in the system, either by reducing the interference and/or by better prediction of the interference.
CoMP operation targets many different deployments, including coordination between sites and sectors in cellular macro deployments, as well as different configurations of heterogeneous deployments, where for instance a macro node coordinates the transmission with pico nodes within the macro coverage area.
There are many different CoMP transmission schemes that are considered, including these examples:                dynamic point blanking where one or more transmission points mute their transmissions on time-frequency resources (TFREs) allocated to UEs experiencing significant interference;        dynamic point selection where the data transmission to a UE switches dynamically (in time and frequency) between different transmission points, so that the various transmission points are fully utilized;        coordinated beamforming where the transmission points coordinate their transmissions in the spatial domain, based on beamforming the transmission power in such a way that the interference to UEs served by neighboring transmission points are suppressed; and        joint transmission where the signal to a UE is simultaneously transmitted from multiple transmission points on the same time/frequency resource, with the aim of joint transmission being an increase in the received signal power and/or a reduction in the received interference, if the cooperating transmission points otherwise would serve some other UEs without taking the joint-transmission UE into consideration.        
CoMP feedback is a common denominator for the CoMP transmission scheme examples given above, and for CoMP systems in general. In this regard, CoMP feedback provides the network with needed CSI information, not only for the serving transmission point, but also for the channels linking the neighboring transmission points to a given UE. For example, by configuring a unique CSI-RS resource per transmission point, a UE can resolve the effective channels for each transmission point by measurements on the corresponding CSI-RS. Here, it should be noted that the UE likely is unaware of the physical presence of any particular transmission point; instead, the UE simply is configured to measure on a particular CSI-RS resource, without knowing the association between the CSI-RS resource and the particular transmission point.
CoMP feedback for LTE Release-11 builds upon per CSI-RS resource feedback, which corresponds to separate reporting of CSI for each of a set of CSI-RS resources. Such a CSI report could for example correspond to a PMI, RI, or CQI, which represent a recommended configuration for a hypothetical downlink transmission over the same antennas used for the associated CSI-RS, or as the RS used for the channel measurement. More generally, the recommended transmission should be mapped to physical antennas in the same way as the reference symbols used for the CSI channel measurement. Potentially there could be interdependencies between the CSI reports; for example, they could be constrained to have the same RI.
Typically there is a one-to-one mapping between a CSI-RS and a transmission point, in which case per CSI-RS resource feedback corresponds to per-TP feedback. That is, a separate PMI/RI/CQI is reported for each transmission point. The considered CSI-RS resources are configured, e.g., by an eNodeB or other network node, as the “CoMP Measurement Set”.
Interference measurements are important for efficient CoMP operation, and it is as important to capture appropriate interference assumptions when determining the CQIs in a CoMP environment, as it is to capture the appropriate received desired signal. In uncoordinated systems, a UE or other wireless device can effectively measure the interference observed from all other transmission points or cells, which will be the relevant interference level in an upcoming data transmission. The UE typically performs such interference measurements by analyzing the residual interference on CRS resources, after subtracting the impact of the CRS signal.
In coordinated systems performing CoMP, such interference measurements become increasingly irrelevant. Most notably, within a coordination cluster, i.e., a set of CoMP transmission points, the coordinating node(s) to a large extent can control which transmission points interfere with a UE in any particular Time-Frequency Resource Element or “TFRE.” Hence, there will be multiple interference hypotheses for the UE, each depending on which transmission points are transmitting data to other UEs.
Release 11 of LTE introduces certain new functionality to improve interference measurements. In particular, it is now agreed that the network will be able to configure a UE to measure interference on a particular Interference Measurement Resource, “IMR”. Each defined IMR identifies a particular set of TFREs that is to be used by the UE for a corresponding interference measurement. The network can thus control the interference seen by a UE on any given IMR by controlling which transmission points within a CoMP cluster transmit on the IMR. If all transmission points in the cluster are muted on that IMR, the IMR may be used by the UE for measuring inter-cluster interference. With respect to a given IMR, the particular pattern of transmitting and non-transmitting transmission points defines the intra-cluster interference hypothesis represented by that IMR.
The network must be able to accurately evaluate the performance of the UE for different CoMP transmission hypotheses; otherwise dynamic coordination becomes meaningless. Thus the network must to be able to track and estimate different intra-cluster interference levels corresponding to the different transmission and blanking hypotheses. See, for example, FIG. 1 in which two transmission points 10-1 and 10-2 operated as a CoMP set of transmission points 10 for a UE 12. The CoMP set also may be referred to as coordination cluster.
FIG. 2 illustrates a table embodying a dynamic transmission-point blanking scheme which may be applied to the transmission points 10-1 and 10-2, also referred to as “TP1” and “TP2”, respectively. In the table, one sees three rows, each corresponding to a different defined IMR, i.e., IMR1, IMR2, and IMR3. As noted, each IMR nominally represents a different interference hypothesis. In the table, a “1” indicates that the TP 10 is transmitting on the IMR and a “0” indicates that the TP 10 is blanked (muted) for the IMR.
Assuming that TP1 is the serving TP 10 for the UE 12, there are two relevant interference hypotheses. In a first relevant hypothesis, the UE 12 sees no interference from the coordinated neighboring transmission point TP2, because TP2 is muted and hence the UE 12 will only experience the signal from its serving transmission point, TP1, in addition to any uncoordinated inter-cluster interference including background noise and interference from uncoordinated devices. In the second relevant hypothesis, the UE 12 sees interference from the neighboring point, TP2, as well as the signal from its serving transmission point TP1 and any inter-cluster interference.
To enable the network to effectively determine whether or not a TP 10 should be muted in this example, the UE 12 can report two CQIs corresponding to the different interference hypotheses. The set of IMRs defined in FIG. 2 represent one way to obtain these multiple CQIs from the UE 12.
In particular, the first IMR, IMR1, corresponds to the first relevant hypothesis mentioned above, i.e., no interference from TP2, and with the implicit assumption that the desired signal originates from the TP1, hence no interference from TP1. Note that the IMR only covers the interference part of the CoMP transmission hypothesis, the desired signal part of the transmission hypothesis is configured using a CSI-RS that defines the channel between the UE 12 and a hypothetical signal source. In other words, to accommodate a CoMP transmission hypothesis where the desired signal originates from TP1, one should use an associated IMR that applies blanking or muting of TP1, represented with “0” in the table, so that the signal from TP1 is not counted as interference.
The second IMR or IMR2 corresponds to the second relevant hypothesis. Again, the “0” blanking or muting of TP1 represents the fact that it is the source of a desired signal rather than an interfering signal, while the “1” in row2/column2 means that TP2 is transmitting an interfering signal on the TFRE of IMR2.
Finally there is also a third IMR defined but this one is of no interest for the illustrated UE 12, because TP1 is the serving TP. It is not interesting to consider it as a source of interference for the UE 12. The network can therefore configure the UE 12 to only measure and report CSI feedback for IMR1 and IMR2.
The above example illustrates the principle of selecting relevant IMRs for a dynamic point blanking CoMP scheme. In such a scheme, the only IMRs that are relevant to a given UE 12 are those IMRs in which the serving TP 10 is muted, because the serving TP 10 is not a source of interference for the served UE 12. Of course, in other CoMP schemes, such as in dynamic point switching in particular, the IMRs representing interference from the serving TP 10 could also be of interest.
With the scheme exemplified in FIG. 2, the likelihood that the different interference hypotheses are actually realized in a downlink transmission is dependent on the system load. For example, at relatively high levels of system loading, it is less likely that all TPs 10 within a given coordination cluster are muted, because muting is costly. That is, muting on the TFREs associated with a given IMR represent a forfeiture of transmission resources that otherwise could be used for data transmission, and such forfeitures obviously become more “costly” as system resources become more precious in higher loading scenarios.
Moreover, for a given UE 12, the network in many cases can make a qualified guess that different interference hypotheses will result in similar performance for the UE 12. For example, if two different interference hypotheses differ only in terms of which weakly interfering TPs 10 are blanked, the actual reception performance at the UE 12 may not differ much between the different interference hypotheses. In an example case, the network receives Reference Signal Received Power, “RSRP”, measurements from the UE 12, which allow it to recognize which TPs 10 in the CoMP cluster are “weak” interferers with respect to the UE.
The network thus may reduce complexity without any appreciable loss in performance by using one IMR to approximate another, in cases where the two IMRs yield similar effective interference scenarios as the UE 12. A consequence of this recognition is that the importance of receiving CSI that is based on a specific IMR varies from UE 12 to UE 12. The importance also depends on the overall traffic situation in the network. For each UE 12, the network may order the IMRs in a priority list, where some IMRs are more important to include in CSI reporting than others.
This priority allows the network to reduce the amount of CSI reporting without compromising on quality. However, the network remains responsible for configuring the transmissions so that the interference measured on the different IMRs corresponds to the desired interference hypotheses. That is, for each IMR, a set of TPs 10 will be muted, and intra-cluster interference only from the remaining coordinated and/or un-coordinated TPs 10 will be present on the IMR.
In the currently known solutions, the data transmission from a specific TP 10 will be present, or muted, on the TFREs of the IMRs where interference from the transmission point is expected to be present, or absent. This scheme is nicely illustrated in the table given in FIG. 3.
The table in FIG. 3 assumes the presence of three TPs 10 in a CoMP cluster, denoted as TP1, TP2 and TP3. For this set of three TPs 10, seven IMRs are needed to capture all possible muting patterns.
Unlike the scheme illustrated in FIG. 2, the IMRs are defined in terms of regular data transmissions by the TPs 10. For a given IMR, a given one of the TPs 10 will either be muted or will be engaging in a regular data transmission. Thus, in the table, one sees that each IMR is defined by a pattern of 0s and Ds, where a “0” entry indicates that the TP 10 is muted for that IMR and a “D” entry indicates that the TP 10 is engaged in a regular data transmission for the IMR, e.g., to another UE 12. In particular, “D1” denotes a regular data transmission by TP1, “D2” denotes a regular data transmission by TP2, and so on.
Now, assume that a given UE 12 is “connected” to TP1. In this serving role, TP1 is not a relevant source of interference with respect to the UE 12. Thus, the interference hypotheses that are potentially relevant to the UE 12 include those represented by IMR1, IMR4, IMR6 and IMR7. Thus, the UE 12 would provide the network with all channel information for all relevant muting combinations by reporting CSI for IMR1, IMR4, IMR6 and IMR7.
Constructing the IMR table around regular data transmissions as exemplified in FIG. 3 is referred to in this disclosure as “Configuration Methodology A” or “CM-A”. A chief advantage of CM-A, as compared to the fixed scheme illustrated in FIG. 2 is that the feedback reporting captures the effects of some TPs 10 being occasionally silent in terms of data transmissions, e.g., because of a low traffic load.
However, there is a significant risk of a UE 12 underestimating interference for one or more IMRs, when dynamic point blanking is applied in the context of CM-A, or, similarly, if the data traffic is highly fluctuating when CM-A is in use. The underestimation of interference occurs because the IMR definitions assume that non-muted TPs 10 will be engaged in regular data transmissions, which will not be true to the extent that there is no data to transmit and these TPs 10 are actually silent on a given IMR. Note that data traffic may fluctuate significantly for any number of reasons. For example, there is a significant fluctuation in data traffic for Transfer Control Protocol or “TCP” connections, which include a slow-start ramping up of traffic flow.
It should also be noted that when the actual blanked/transmitting pattern of a given IMR differs from its nominally defined pattern because of dynamic point blanking, the IMR generally will correspond to the interference hypothesis covered by another IMR. Thus, dynamic point blanking can cause a loss of uniqueness between or among the defined IMRs.
Of course, the network is aware of any dynamic muting that occurs on the IMR in question and the controlling node(s) could be instructed to disregard CSI reports from UEs 12 that are made on IMRs that have been disrupted by dynamically muted transmissions. Even so, it will be recognized that ignoring such CSI reports represents waste of uplink resources and a waste of valuable opportunities to acquire CSI.
Traffic fluctuations can be more problematic with respect to CM-A. For example, when the load in the network is low, there may be many TPs 10 that are silent over longer periods because of low UE density. When a TP 10 is silent, it becomes impossible to acquire CSI feedback indicating what would happen if the TP 10 suddenly began transmitting data, e.g., because an active UE 12 is handed over to it, or because a previously idle UE 12 returns to the active connection state and begins downloading data. Furthermore, the IMRs that have been configured to capture interference variations due to the on/off behavior of the TP will essentially measure the same interference level.
This problem can be addressed to a limited extent by reconfiguring the UEs 12, using RRC signaling, i.e., by reconfiguring specific UEs 12 as regards the IMRs on which they measure and report CSI. Such reconfiguration would be needed as soon as the resource utilization in the system varies, e.g., such as when new UEs 12 arrive or leave. RRC reconfiguration is however a relatively lengthy and cumbersome procedure and therefore is not a suitable mechanism for dealing with dynamic traffic variations. A known alternative to the CM-A approach decouples the signals transmitted on IMRs from the regular data transmissions at the TPs 10. In this second configuration methodology, which is termed “Configuration Method B” or “CM-B”, the network maintains IMRs with fixed interference patterns that cover all relevant interference hypotheses—i.e., fixed and distinct combinations of on/off coordination of the different TPs 10 within the coordination cluster.
Such an approach is shown in FIG. 4, again using the example of three TPs 10 in a coordination cluster, denoted as TP1, TP2 and TP3. Again, seven IMRs are needed to capture all possible muting patterns. A “0” entry indicates that the TP 10 is silent in the corresponding IMR, and a “1” entry indicates that an interfering signal is transmitted by the TP 10 on the IMR, independent of any regular data transmission). A UE 12 that is served by TP1 could for instance be configured to report CSI based on IMRs 1, 4, 6, and 7, in order to capture all muting combinations of the interfering TPs 10. The CM-B configuration hence allows a UE 12 to measure IMRs and report corresponding relevant CSI regardless of whether the system load is low or high—i.e., independent of traffic fluctuations at the various TPs 10.
Thus, a primary benefit of the CM-B configuration as compared to the CM-A configuration is that the interference patterns represented by the different IMRs are invariant to fluctuations in data traffic caused by changes in loading, etc. That is, the IMR patterns remain distinct, meaning that a given UE 12 is able to measure and report CSI for a unique pattern of interference on each of its relevant IMRs. This approach means that no CSI report has to be disregarded and that none of the IMRs will, in actuality, overlap, even during times of low resource utilization within the system. Thus, the network will always be able to receive CSI reports for all IMRs that are relevant to a given UE 12. Here, a “relevant” IMR is an IMR that represent an interference hypothesis that is deemed relevant by the network, e.g., an interference hypothesis that is likely to be realized and that provides important information about the strongest interfering TPs 10 for the UE 12 that is under consideration.
However, the CM-B configuration has a number of disadvantages. For example, it is recognized herein that the configuration fails to capture the concept of uneven likelihoods associated with the interference hypotheses represented by different IMRs. Indeed, in some sense, the CM-B configuration treats all IMRs as equally important. To illustrate why this can be disadvantageous, consider a UE 12 that can only afford to feed back one CSI report each reporting instance. The one CSI report should be based on the IMR that corresponds to the most likely interference hypothesis, which typically is the interference hypothesis that is most similar to the interference seen on the regular data resource elements.
Unfortunately, the most relevant IMR changes as a function of changing traffic patterns within the coordination cluster. To keep the UE 12 reporting on the most relevant IMR thus requires an RRC-based reconfiguration any time there is a meaningful change in the traffic patterns within the coordination cluster. The CM-A configuration avoids this problem in that a UE 12 feeding back only one CSI report per reporting interval will base that report on the IMR where only its own serving TP 10 is muted and regular data transmissions by the other, interfering TPs 10 are present—e.g., IMR1 in row 1 of the table shown in FIG. 4.
It is further recognized herein that the CM-B configuration has a similar problem in the case where a UE 12 is configured to report multiple CSI reports, where a first report determines one or more properties of the other reports. For instance, it is advantageous to use the same transmission rank in all CSI reports, because the scheduling towards a UE rank cannot vary in frequency. Thus, the controlling network node(s) can use the multiple CSI reports for frequency selective scheduling by, for example, scheduling a transmission based on CSI from one report on certain subbands and CSI from another report on other subbands, because all such reports are based on the same rank.
In order to achieve this goal, the system may be configured such that the CSI report corresponding to the most likely interference hypothesis for a UE 12 determines the properties, including rank, of the other CSI reports. This will effectively minimize any negative aspect of restricting the properties because the most relevant CSI report remains unrestricted. Using CM-B, most likely the CSI process corresponding to the most relevant CSI report will have to be reconfigured with a new IMR if a second UE 12 is activated for downlink transmission from a previously inactive TP 10.