6,563 research outputs found

    The Ergodic Capacity of Phase-Fading Interference Networks

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    We identify the role of equal strength interference links as bottlenecks on the ergodic sum capacity of a KK user phase-fading interference network, i.e., an interference network where the fading process is restricted primarily to independent and uniform phase variations while the channel magnitudes are held fixed across time. It is shown that even though there are K(K−1)K(K-1) cross-links, only about K/2K/2 disjoint and equal strength interference links suffice to determine the capacity of the network regardless of the strengths of the rest of the cross channels. This scenario is called a \emph{minimal bottleneck state}. It is shown that ergodic interference alignment is capacity optimal for a network in a minimal bottleneck state. The results are applied to large networks. It is shown that large networks are close to bottleneck states with a high probability, so that ergodic interference alignment is close to optimal for large networks. Limitations of the notion of bottleneck states are also highlighted for channels where both the phase and the magnitudes vary with time. It is shown through an example that for these channels, joint coding across different bottleneck states makes it possible to circumvent the capacity bottlenecks.Comment: 19 page

    Interference Mitigation in Large Random Wireless Networks

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    A central problem in the operation of large wireless networks is how to deal with interference -- the unwanted signals being sent by transmitters that a receiver is not interested in. This thesis looks at ways of combating such interference. In Chapters 1 and 2, we outline the necessary information and communication theory background, including the concept of capacity. We also include an overview of a new set of schemes for dealing with interference known as interference alignment, paying special attention to a channel-state-based strategy called ergodic interference alignment. In Chapter 3, we consider the operation of large regular and random networks by treating interference as background noise. We consider the local performance of a single node, and the global performance of a very large network. In Chapter 4, we use ergodic interference alignment to derive the asymptotic sum-capacity of large random dense networks. These networks are derived from a physical model of node placement where signal strength decays over the distance between transmitters and receivers. (See also arXiv:1002.0235 and arXiv:0907.5165.) In Chapter 5, we look at methods of reducing the long time delays incurred by ergodic interference alignment. We analyse the tradeoff between reducing delay and lowering the communication rate. (See also arXiv:1004.0208.) In Chapter 6, we outline a problem that is equivalent to the problem of pooled group testing for defective items. We then present some new work that uses information theoretic techniques to attack group testing. We introduce for the first time the concept of the group testing channel, which allows for modelling of a wide range of statistical error models for testing. We derive new results on the number of tests required to accurately detect defective items, including when using sequential `adaptive' tests.Comment: PhD thesis, University of Bristol, 201

    Error exponent of amplify and forward relay networks in presence of I.I.D. interferers

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    © 2014 IEEE. In this paper, we derive the random coding error exponent of amplify-and-forward (AF) relay networks in presence of arbitrary number of independent and identically distributed (i.i.d.) interferers both at the relay and the destination. Multiuser networks are common examples of interference limited networks. We derive the ergodic capacity of the network and present simulation results on the performance of the network where we compare the capacity and error exponent performance of interference limited networks with noise limited networks. Numerical results show that noise limited networks outperform interference limited networks even when only a very few interferers exist in the network

    Asymptotic analysis of precoded small cell networks

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    International audienceIn this paper, we study precoded MIMO based small cell networks. We derive the theoretical sum-rate capacity, when multi-antenna base stations transmit precoded information to its multiple single-antenna users in the presence of inter- cell interference from neighboring cells. Due to an interference limited scenario, increasing the number of antennas at the base stations does not yield necessarily a linear increase of the capacity. We assess exactly the effect of multi-cell interference on the capacity gain for a given interference level. We use recent tools from random matrix theory to obtain the ergodic sum-rate capacity, as the number of antennas at the base station, number of users grow large. Simulations confirm the theoretical claims and also indicate that in most scenarios the asymptotic derivations applied to a finite number of users give good approximations of the actual ergodic sum-rate capacity

    Performance Analysis of SSK-NOMA

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    In this paper, we consider the combination between two promising techniques: space-shift keying (SSK) and non-orthogonal multiple access (NOMA) for future radio access networks. We analyze the performance of SSK-NOMA networks and provide a comprehensive analytical framework of SSK-NOMA regarding bit error probability (BEP), ergodic capacity and outage probability. It is worth pointing out all analysis also stand for conventional SIMO-NOMA networks. We derive closed-form exact average BEP (ABEP) expressions when the number of users in a resource block is equal to i.e., L=3L=3. Nevertheless, we analyze the ABEP of users when the number of users is more than i.e., L≥3L\geq3, and derive bit-error-rate (BER) union bound since the error propagation due to iterative successive interference canceler (SIC) makes the exact analysis intractable. Then, we analyze the achievable rate of users and derive exact ergodic capacity of the users so the ergodic sum rate of the system in closed-forms. Moreover, we provide the average outage probability of the users exactly in the closed-form. All derived expressions are validated via Monte Carlo simulations and it is proved that SSK-NOMA outperforms conventional NOMA networks in terms of all performance metrics (i.e., BER, sum rate, outage). Finally, the effect of the power allocation (PA) on the performance of SSK-NOMA networks is investigated and the optimum PA is discussed under BER and outage constraints

    Capacity limits of bursty interference channels

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    Mención Internacional en el título de doctorThis dissertation studies the effects of interference burstiness in the transmission of data in wireless networks. In particular, we investigate the effects of this phenomenon on the largest data rate at which one can communicate with a vanishing small probability of error, i.e., on channel capacity. Specifically, we study the capacity of two different channel models as described in the next sections. Linear deterministic bursty interference channel. First, we consider a two-user linear deterministic bursty interference channel (IC), where the presence or absence of interference is modeled by a block- independent and identically distributed (IID) Bernoulli process that stays constant for a duration of T consecutive symbols (this is sometimes referred to as a coherence block) and then changes independently to a new interference state. We assume that the channel coefficients of the communication and interference links remain constant during the whole message transmission. For this channel, we consider both its quasi-static setup where the interference state remains constant during the whole transmission of the codeword (which corresponds to the case whether the blocklength N is smaller than T) and its ergodic setup where a codeword spans several coherence blocks. For the quasi-static setup, we follow the seminal works by Khude, Prabhakaran and Viswanath and study the largest sum rate of a coding strategy that provides reliable communication at a basic (or worstcase) rate R and allows an increased (opportunistic) rate ΔR in absence of interference. For the ergodic scenario, we study the largest achievable sum rate as commonly considered in the multi-user information theory literature. We study how (noncausal) knowledge of the interference state, referred to as channel state information (CSI), affects the sum capacity. Specifically, for both scenarios, we derive converse and achievability bounds on the sum capacity for (i) local CSI at the receiverside only; (ii) when each transmitter and receiver has local CSI, and (iii) global CSI at all nodes, assuming both that interference states are independent of each other and that they are fully correlated. Our bounds allow us to identify regions and conditions where interference burstiness is beneficial and in which scenarios global CSI improves upon local CSI. Specifically, we show the following: • Exploiting burstiness: For the quasi-static scenario we have shown that in presence of local CSI, burstiness is only beneficial if the interference region is very weak or weak. In contrast, for global CSI, burstiness is beneficial for all interference regions, except the very strong interference region, where the sum capacity corresponds to that of two parallel channels without interference. For the ergodic scenario, we have shown that, under global CSI, burstiness is beneficial for all interference regions and all possible values of p. For local CSI at the receiver-side only, burstiness is beneficial for all values of p and for very weak and weak interference regions. However, for moderate and strong interference regions, burstiness is only of clear benefit if the interference is present at most half of the time. • Exploiting CSI: For the quasi-static scenario, local CSI at the transmitter is not beneficial. This is in stark contrast to the ergodic scenario, where local CSI at the transmitter-side is beneficial. Intuitively, in the ergodic scenario the input distributions depend on the realizations of the interference states. Hence, adapting the input distributions to these realizations increases the sum capacity. In contrast, in the quasi-static case, the worst-case scenario (presence of interference) and the best-case scenario (absence of interference) are treated separately. Hence, there is no difference to the case of having local CSI only at the receiver side. Featuring global CSI at all nodes yields an increased sum rate for both the quasi-static and the ergodic scenarios. The joint treatment of the quasi-static and the ergodic scenarios allows us to thoroughly compare the sum capacities of these two scenarios. While the converse bounds for the quasi-static scenario and local CSI at the receiver-side appeared before in the literature, we present a novel proof based on an information density approach and the Verd´u-Han lemma. This approach does not only allow for rigorous yet clear proofs, it also enables more refined analyses of the probabilities of error that worst-case and opportunistic messages can be decoded correctly. For the converse bounds in the ergodic scenario, we use Fano’s inequality as the standard approach to derive converse bounds in the multi-user information theory literature. Bursty noncoherent wireless networks. The linear deterministic model can be viewed as a rough approximation of a fading channel, which has additive and multiplicative noise. The multiplicative noise is referred to as fading. As we have seen in the previous section, the linear deterministic model provides a rough understanding of the effects of interference burstiness on the capacity of the two-user IC. Now, we extend our analysis to a wireless network with a very large number of users and we do not approximate the fading channel by a linear deterministic model. That is, we consider a memoryless flat-fading channel with an infinite number of interferers. We incorporate interference burstiness by an IID Bernoulli process that stays constant during the whole transmission of the codeword. The channel capacity of wireless networks is often studied under the assumption that the communicating nodes have perfect knowledge of the fading coefficients in the network. However, it is prima-facie unclear whether this perfect knowledge of the channel coefficients can actually be obtained in practical systems. For this reason, we study in this dissertation the channel capacity of a noncoherent model where the nodes do not have perfect knowledge of the fading coefficients. More precisely, we assume that the nodes know only the statistics of the channel coefficients but not their realizations. We further assume that the interference state (modeling interference burstiness) is known non-causally at the receiver-side only. To the best of our knowledge, one of the few works that studies the capacity of noncoherent wireless networks (without considering interference burstiness) is by Lozano, Heath, and Andrews. Inter alia, Lozano et al. show that in the absence of perfect knowledge of the channel coefficients, if the channel inputs are given by the square-root of the transmit power times a power-independent random variable, and if interference is always present (hence, it is non-bursty), then the achievable information rate is bounded in the signal-to-noise ratio (SNR). However, the considered inputs do not necessarily achieve capacity, so one may argue that the information rate is bounded in the SNR because of the suboptimal input distribution. Therefore, in our analysis, we allow the input distribution to change arbitrarily with the SNR. We analyze the asymptotic behavior of the channel capacity in the limit as the SNR tends to infinity. We assume that all nodes (transmitting and interfering) use the same codebook. This implies that each node is transmitting at the same rate, while at the same time it keeps the analysis tractable. We demonstrate that if the nodes do not cooperate and if the variances of the path gains decay exponentially or slower, then the achievable information rate remains bounded in the SNR, even if the input distribution is allowed to change arbitrarily with the transmit power, irrespective of the interference burstiness. Specifically, for this channel, we show the following: • The channel capacity is bounded in the SNR. This suggests that noncoherent wireless networks are extremely power inefficient at high SNR. • Our bound further shows that interference burstiness does not change the behavior of channel capacity. While our upper bound on the channel capacity grows as the channel becomes more bursty, it remains bounded in the SNR. Thus, interference burstiness cannot be exploited to mitigate the power inefficiency at high SNR. Possible strategies that could mitigate the power inefficiency of noncoherent wireless networks and that have not been explored in this thesis are cooperation between users and improved channel estimation strategies. Indeed, coherent wireless networks, in which users have perfect knowledge of the fading coefficients, have a capacity that grows to infinity with the SNR. Furthermore, for such networks, the most efficient transmission strategies, such as interference alignment, rely on cooperation. Our results suggest that these two strategies may be essential to obtain an unbounded capacity in the SNR.Programa Oficial de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Ignacio Santamaría Caballero.- Secretario: David Ramírez García, David.- Vocal: Paul de Kerre

    Interference Analysis for Vehicle-to-Vehicle Communications at 28 GHz

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    High capacity and ultra-reliable vehicular communication are going to be important aspects of beyond 5G communication networks. However, the vehicular communication problem becomes complex at a large scale when vehicles are roaming on the road, while simultaneously communicating with each other. Moreover, at higher frequencies (like 28 GHz), the dynamics of vehicular communication completely shift towards unpredictability and low-reliability. These factors may result in high packet error and a large amount of interference, resulting in regular disruptions in communications. A thorough understanding of performance variations is the key to moving towards the next generation of vehicular networks. With this intent, this article aims to provide a comprehensive interference analysis, wherein the closed-form expressions of packet error probability (PEP) and ergodic capacity are derived. Using the expression of the PEP, diversity analysis is provided which unveils the impact of channel nonlinearities on the performance of interference-constrained vehicular networks. The insights provided here are expected to pave the way for reliable and high capacity vehicular communication networks
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