MIMO IV: multiuser communication in .NET Creation barcode 3/9 in .NET MIMO IV: multiuser communication

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MIMO IV: multiuser communication use none none integration toattach none in none .NET Framework Downlink wi none for none th multiple receive antennas Each user gets receive beamforming gain but reduced multiuser diversity gain. Downlink with multiple transmit antennas No CSI at the base-station: single spatial degree of freedom. Full CSI: the uplink downlink duality principle makes this situation analogous to the uplink with multiple receive antennas and now there are up to nt spatial degrees of freedom.

Partial CSI at the base-station: the same spatial degrees of freedom as the full CSI scenario can be achieved by a modification of the opportunistic beamforming scheme: multiple spatially orthogonal beams are sent out and multiple users are simultaneously scheduled on these beams.. 10.5.1 Inter-cell interference management Consider th none none e multiple receive antenna uplink with users operating in SDMA mode. We have seen that successive cancellation is an optimal way to handle interference among the users within the same cell. However, this technique is not suitable to handle interference from neighboring cells: the out-of-cell transmissions are meant to be decoded by their nearest base-stations and the received signal quality is usually too poor to allow decoding at base-stations further away.

On the other hand, linear receivers such as the MMSE do not decode the information from the interference and can be used to suppress out-of-cell interference. The following model captures the essence of out-of-cell interference: the received signal at the antenna array (y) comprises the signal (x) of the user of interest (with the signals of other users in the same cell successfully canceled) and the out-of-cell interference (z): y = hx + z (10.81).

Here h is t he received spatial signature of the user of interest. One model for the random interference z is as 0 Kz , i.e.

, it is colored Gaussian noise with covariance matrix Kz . For example, if the interference originates from just one out-of-cell transmission (with transmit power, say, q) and the base-station has an estimate of the received spatial signature of the interfering transmission (say, g), then the covariance matrix is qgg + N0 I (10.82).

taking into account the structure of the interference and the background additive Gaussian noise. 10.5 Multiple antennas in cellular networks Once such a none none model has been adopted, the multiple receive antennas can be used to suppress interference: we can use the linear MMSE receiver developed in Section 8.3.3 to get the soft estimate (cf.

(8.61)):. 1 x = vmmse y = h Kz y (10.83). The express ion for the corresponding SINR is in (8.62). This is the best SINR possible with a linear estimate.

When the interfering noise is white, the operation is simply traditional receive beamforming. On the other hand, when the interference is very large and not white then the operation reduces to a decorrelator: this corresponds to nulling out the interference. The effect of channel estimation error on interference suppression is explored in Exercise 10.

23. In the uplink, the model for the interference depends on the type of multiple access. In many instances, a natural model for the interference is that it is white.

For example, if the out-of-cell interference comes from many geographically spread out users (this situation occurs when there are many users in SDMA mode), then the overall interference is averaged over the multiple users spatial locations and white noise is a natural model. In this case, the receive antenna array does not explicitly suppress out-of-cell interference. To be able to exploit the interference suppression capability of the antennas, two things must happen: The number of simultaneously transmitting users in each cell should be small.

For example,in a hybrid SDMA/TDMA strategy, the total number of users in each cell may be large but the number of users simultaneously in SDMA mode is small (equal to or less than the number of receive antennas). The out-of-cell interference has to be trackable. In the SDMA/TDMA system, even though the interference at any time comes from a small number of users, the interference depends on the geographic location of the interfering user(s), which changes with the time slot.

So either each slot has to be long enough to allow enough time to estimate the color of the interference based only on the pilot signal received in that time slot, or the users are scheduled in a periodic manner and the interference can be tracked across different time slots. An example of such a system is described in Example 10.1.

On the other hand, interference suppression in the downlink using multiple receive antennas at the mobiles is different. Here the interference comes from a few base-stations of the neighboring cells that reuse the same frequency, i.e.

, from fixed specific geographic locations. Now, an estimate of the covariance of the interference can be formed and the linear MMSE can be used to manage the inter-cell interference. We now turn to the role of multiple antennas in deciding the optimal amount of frequency reuse in the cellular network.

We consider the effect.
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