Interference is the limiting factor in the performance of CDMA and WCDMA wireless networks. Field conditions such as fading and multipath defeat all attempts to maintain orthogonality between traffic and control channels in multi-access voice and data systems based on CDMA and WCDMA standards. The lack of orthogonality leads to interference and a consequent reduction in signal-to-interference and noise ratio (SINR). Thus, CDMA and WCDMA are interference-limited rather than noise-limited. As a consequence:

• After multipath resolution with a RAKE receiver, every resolved baseband path contains interchannel interference (ICI) and intersymbol interference (ISI) from every other path.

• This produces a bit-error-rate (BER) higher than a target energy-to-noise density ratio (Eb/No) would predict, requiring a) increased signal strength and SINR, b) reduced traffic-loading and/or c) reduced bit-rate to maintain network quality of service (QoS).

• Transmit power increases because neighboring devices ask for more power to contend with more interference.

• Overall network capacity should be maximized by having each device use the minimum required transmission power so that the interference caused to other devices in the network is minimized.

There is a body of work for interference cancellation and multi-user detection suggesting that all interference effects can be managed with signal processing if the channel can be accurately estimated and the optimal signal-processing solution can be implemented at the symbol rate for voice and data. Neither of these ideals is achievable. The TensorComm approach approximates the optimum solution by factoring interference cancellation into a sequence of signal-processing steps that remove ISI and ICI.

The company has filed more than 75 patents in this area and indicates its strength is to blend advanced signal processing with existing transceiver architectures for CDMA and WCDMA modems.

The example illustrated in Figure 1 describes the application of ICT. Consider y to be the complex baseband signal arriving at a handset (after reception at the antenna and downconversion). This signal can be resolved into multiple components that represent the different paths arriving at the antenna, plus thermal noise.

For example, we could represent the complex signal in path 1 as:

where s₁ and s₂ are signals from two different paths from base station 1, while s₃ and s₄ are multipath signals from base station 2 in soft hand-off. n is the thermal noise in the received signal.

A conventional RAKE receiver assigns these paths to different fingers, which then recover the message by applying the correct aligned codes for recovery of the transmitted symbol. While the design and selection of the codes attempts to minimize the cross-correlation of the desired codes with the codes of other paths, the presence of multipath and hand-off defeats orthogonality and produces non-zero cross-correlation between signal components.

Let the codes for the channels of interest be:

x₁, x₂, x₃ and x₄ for the respective paths.

The RAKE receiver then recovers the symbols

m₁, m₂, m₃ and m₄ by computing inner products with the corresponding codes. The estimated symbol in path 1, is obtained using the inner product or correlation

where m₁ is the symbol of interest in path 1, i₁ is interference and n₁ is noise.

That is,

Similarly, each path experiences interference from all the other paths:

The combiner combines the symbol estimates from each path to arrive at a soft decision, usually using a maximal ratio combiner:

where β₁, β₂, β₃ and β₄ are the maximal ratio coefficients associated with each path (usually pilot amplitudes).

Because of the correlations between the multipath signals s_i and the codesx_j, the symbol estimates contain interference from all paths.

The estimated SINR, also referred to as Ec/Io, is the ratio of the signal energy (Ec) to the total noise and interference (Io) in the system. Let's call I_j the variance (or power) of interference i_j, and σ² the variance of the noise. Then ignoring correlation between interferences, a crude but descriptive estimate of SINR is:

In an ICT-enabled handset, the interference in the signal y₁ is canceled, so that the application of the desired code yields a smaller interference term. Thus,

where y_1ICT is the signal for path 1 with interference canceled.

That is,

where the variance (or power) of ε₁i₁ is much smaller than the power of i₁, and α₁ is approximately 1. Therefore, the maximal ratio combined symbol estimate is:

The new estimated SINR is:

The ICT gain G can be roughly estimated as:

To illustrate, if all ε_j² are roughly equal to ε² <<1, then the gain is:

This gain is realized without impacting the diversity that multipath brings or from the gain due to hand-off. Interference cancellation preserves all the advantages of the system while increasing SINR. In hand-off, the receiver resolves multipaths with higher SINRs than it would have in the absence of ICT.

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