Abstract
In the context of multiuser detection for the DS-CDMA uplink, out-of-cell interference is usually treated as Gaussian noise, possibly mitigated by overlaying a long random cell code on top of symbol spreading. Different cells use statistically independent long codes, thereby providing means for statistical out-of-cell interference suppression. When the total number of (in-cell plus out-of-cell) users is less than the spreading gain, subspace identification techniques are applicable. If the base station is equipped with multiple antennas, then completely blind identification is possible via three-dimensional low-rank decomposition. This works with more users than spreading and antennas, but a purely algebraic solution is missing. In this paper, we develop an algebraic solution under the premise that the codes of the in-cell users are known. The codes of out-of-cell users and all array steering vectors are unknown. In this pragmatic scenario, we show that in addition to algebraic solution, better identifiability is possible. Our approach yields the best known identifiability result for three-dimensional low-rank decomposition when one of the three component matrices is partially known, albeit noninvertible. Simulations show that the proposed identification algorithm remains close to the pertinent asymptotic (symbol-independent) Cramer-Rao bound, which is also derived herein.
Highlights
In the context of uplink reception for cellular DS-CDMA systems, interference can be classified as either (i) interchip (ICI) and intersymbol (ISI) self-interference, (ii) in-cell multiuser access interference, or (iii) out-of-cell multiuser access interference
Assuming that (i) the codes of the in-cell users are known, (ii) the total number of users is less than the spreading gain and the combined spreading code matrix is full column rank, and (iii) given the correlation matrix of the vector of chip samples taken over a symbol interval, it is possible to cancel out the effect of out-of-cell users [3], adopt linear or nonlinear solutions for in-cell detection
Out-of-cell interference in DS-CDMA systems is usually treated as noise, possibly mitigated using random cell codes
Summary
In the context of uplink reception for cellular DS-CDMA systems, interference can be classified as either (i) interchip (ICI) and intersymbol (ISI) self-interference, (ii) in-cell multiuser access interference (commonly referred to as MUI or MAI), or (iii) out-of-cell multiuser access interference. This is easy to see for a single out-of-cell user It follows that random cell codes work reasonably well in relatively underloaded systems with large spreading gain (e.g., 128 chips/symbol), but performance can suffer from near-far effects, and cell codes cannot help identify out-of-cell transmissions. Assuming that (i) the codes of the in-cell users are known, (ii) the total number of (in-cell plus out-of-cell) users is less than the spreading gain and the combined spreading code matrix is full column rank, and (iii) given the correlation matrix of the vector of chip samples taken over a symbol interval, it is possible to cancel out the effect of out-of-cell users [3], adopt linear or nonlinear solutions for in-cell detection This approach is appealing, but it has two drawbacks. E(·) denotes the expectation operator. f , g denotes the L2 inner product between functions f and g
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