Interference Mitigation via Joint Detection

Abstract

This paper addresses the design of optimal and near-optimal detectors in an interference channel with fading and with additive white Gaussian noise (AWGN), where the transmitters employ discrete modulation schemes as in practical communication scenarios. The conventional detectors typically either ignore the interference or successively detect and then cancel the interference, assuming that the desired signal and/or the interference are Gaussian. This paper quantifies the significant performance gain that can be obtained if the detectors explicitly take into account the modulation formats of the desired and the interference signals. This paper first describes the optimal maximumlikelihood (ML) detector that minimizes the probability of detection error for a given modulation scheme, and the joint minimum-distance (MD) detector, which is a lower-complexity approximation of the ML detector. It is then demonstrated by analysis and by simulation that in an AWGN channel, while interference-ignorant and successive interference cancellation detectors are both prone to error floors, the optimal ML and joint MD detectors are not. This paper further analyzes the performance of joint detection in a Rayleigh fading environment. It is demonstrated that the joint detector can achieve symbol error rates that have the same dependence on the received signal-to-noise ratio (SNR) as if the channel were interference free. Thus, the performance of joint detection is fundamentally limited by the SNR rather than the signal-to-interference ratio (SIR). Moreover, the joint detector enables the use of transmit diversity schemes to achieve the same diversity order as in the absence of interference. These results show that the use of interference-aware detectors can significantly alleviate the effect of interference thereby improving the achievable rates and the reliability of future wireless systems. Index Termsinterference channel, maximum likelihood detection, joint detection, inter-cell interference, crosstalk.J. Lee is with Mobile Solutions Lab,

Near ML Modulation Classification

“…Since the approximationl n substantially underestimates the average log-likelihood l n , it is significantly biased at low and intermediate SNR while the use ofl n can yield good classification performance at high SNR. 1 This approximation is studied in [6], where it is also suggested (but not explicitly demonstrated) to use the second largest exponential term inside the logarithm at the first line of (7) and ignore the remaining bias. For this, we need to compute the Jacobian logarithm based on a LUT anyway [12], which may not eliminate bias completely at low and some intermediate SNR.…”

“…In [1], the benefit of joint detection has been investigated assuming that interference modulation is known. If not, for mitigation, interference modulation needs to be identified using a modulation classifier beforehand.…”

Adaptive Sliding-Window Coded Modulation in Cellular Networks

“…Both schemes are simple and can utilize existing p2p coding techniques. Exploiting the modulation information of interfering signals, IAN can be enhanced to the interference-aware detection (IAD) scheme [2], the signaling and network-side operations of which are now standardized in recently completed Third-Generation Partnership Project (3GPP) Release 12 [3]. Both IAN and IAD achieve fairly good performance when interference is weak, but their performance degrades as interference becomes stronger.…”

Comparative study of various multiuser detection and base-station cooperation schemes for uplink multicell systems

“…The authors in [8] have considered the MCP based on the group MMSE-SIC, when assuming that each BS has multiple antennas but supports only one user. Most recently, a joint detection scheme has been investigated in [9], which turns an interference-limited system into a noise-limited system. Accordingly, intercell interference is exploited by acquiring the knowledge about the modulation formats of interfering users.…”