1,631 research outputs found

    Interference Networks with Point-to-Point Codes

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    The paper establishes the capacity region of the Gaussian interference channel with many transmitter-receiver pairs constrained to use point-to-point codes. The capacity region is shown to be strictly larger in general than the achievable rate regions when treating interference as noise, using successive interference cancellation decoding, and using joint decoding. The gains in coverage and achievable rate using the optimal decoder are analyzed in terms of ensemble averages using stochastic geometry. In a spatial network where the nodes are distributed according to a Poisson point process and the channel path loss exponent is β>2\beta > 2, it is shown that the density of users that can be supported by treating interference as noise can scale no faster than B2/βB^{2/\beta} as the bandwidth BB grows, while the density of users can scale linearly with BB under optimal decoding

    Recovering Multiplexing Loss Through Successive Relaying Using Repetition Coding

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    In this paper, a transmission protocol is studied for a two relay wireless network in which simple repetition coding is applied at the relays. Information-theoretic achievable rates for this transmission scheme are given, and a space-time V-BLAST signalling and detection method that can approach them is developed. It is shown through the diversity multiplexing tradeoff analysis that this transmission scheme can recover the multiplexing loss of the half-duplex relay network, while retaining some diversity gain. This scheme is also compared with conventional transmission protocols that exploit only the diversity of the network at the cost of a multiplexing loss. It is shown that the new transmission protocol offers significant performance advantages over conventional protocols, especially when the interference between the two relays is sufficiently strong.Comment: To appear in the IEEE Transactions on Wireless Communication

    Successive Interference Cancellation and Fractional Frequency Reuse For LTE Uplink Communications

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    Cellular networks are increasingly densified to deal with fast growing wireless traffic. Interference mitigation plays a key role for the dense cellular networks. Successive interference cancellation (SIC) and fractional frequency reuse (FFR) are two representative inter-cell interference (ICI) mitigation techniques. In this paper we study the application of both SIC and FFR for LTE uplink networks, and develop an analytical model to investigate their interactions and impact on network performance. The performance gains with FFR and SIC are related to key system functionalities and variables, such as SIC parameters, FFR bandwidth partition, uplink power control and sector antennas. The ICIs from individual cell sectors are approximated by log-normal random variables, which enables low complexity computation of the aggregate ICI with FFR and SIC. Then network performance of site throughput and outage probability is computed. The model is fast and has small modelling deviation, which is validated by system level simulations. Numerical results show that both SIC and FFR can largely improve network performance, but SIC has an impact over FFR. In addition, most of the network performance gains with SIC could be obtained with a small number of SIC stages applied to a few sectors

    Coded DS-CDMA Systems with Iterative Channel Estimation and no Pilot Symbols

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    In this paper, we describe direct-sequence code-division multiple-access (DS-CDMA) systems with quadriphase-shift keying in which channel estimation, coherent demodulation, and decoding are iteratively performed without the use of any training or pilot symbols. An expectation-maximization channel-estimation algorithm for the fading amplitude, phase, and the interference power spectral density (PSD) due to the combined interference and thermal noise is proposed for DS-CDMA systems with irregular repeat-accumulate codes. After initial estimates of the fading amplitude, phase, and interference PSD are obtained from the received symbols, subsequent values of these parameters are iteratively updated by using the soft feedback from the channel decoder. The updated estimates are combined with the received symbols and iteratively passed to the decoder. The elimination of pilot symbols simplifies the system design and allows either an enhanced information throughput, an improved bit error rate, or greater spectral efficiency. The interference-PSD estimation enables DS-CDMA systems to significantly suppress interference.Comment: To appear, IEEE Transactions on Wireless Communication

    Massive Random Access with Common Alarm Messages

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    The established view on massive IoT access is that the IoT devices are activated randomly and independently. This is a basic premise also in the recent information-theoretic treatment of massive access by Polyanskiy. In a number of practical scenarios, the information from IoT devices in a given geographical area is inherently correlated due to a commonly observed physical phenomenon. We introduce a model for massive access that accounts for correlation both in device activation and in the message content. To this end, we introduce common alarm messages for all devices. A physical phenomenon can trigger an alarm causing a subset of devices to transmit the same message at the same time. We develop a new error probability model that includes false positive errors, resulting from decoding a non-transmitted codeword. The results show that the correlation allows for high reliability at the expense of spectral efficiency. This reflects the intuitive trade-off: an access from a massive number can be ultra-reliable only if the information across the devices is correlated.Comment: Extended version of conference submissio
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