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In wireless networks, the link connectivity may be intermittent due to shadowing, burstiness of data arrival, or uncoordinated resource allocation. In this paper, we model the intermittence of links as Bernoulli distributed random channel states, termed intermittence channel states, and study the impact of the corresponding channel state information at the transmitter (CSIT) in a two-user Gaussian broadcast channel (BC). Moreover, due to the heterogeneous timeliness of intermittence channel states, the CSIT considered in this paper is hybrid. More specifically, the CSIT of each link can be perfectly (causally or non-causally) available, delayed, or not available. When the links are connected, we adopt a general setting that the received signal-to-noise ratios can be different. Our contribution is the characterization of the capacity regions of intermittent Gaussian BC to within bounded gaps for all combinations of hybrid CSIT, except for scenario DN (delayed CSIT of receiver 1, no CSIT of receiver 2). For scenario DN, we propose an opportunistic physical layer network coding scheme that achieves a strictly larger degree-of-freedom (DoF) region than the no-CSIT DoF region. As a corollary, single-user CSIT is able to increase the sum DoF for intermittent Gaussian BC (also the capacity region for the erasure BC, as a by-product). This result is in sharp contrast to the recent negative result by Davoodi and Jafar, where it is shown that for fast-fading multiple-input single-output BC with continuous channel states, single-user CSIT does not help at all in terms of sum DoF. [ABSTRACT FROM AUTHOR]

Consider a (multiple-access) wireless communication system where users are connected to a unique base station over a shared-spectrum radio links. Each user has a fixed number k of bits to send to the base station, and his signal gets attenuated by a random channel gain (quasi-static fading). In this paper we consider the many-user asymptotics of Chen-Chen-Guo’2017, where the number of users grows linearly with the blocklength. Differently, though, we adopt a per-user probability of error (PUPE) criterion (as opposed to classical joint-error probability criterion). Under PUPE the finite energy-per-bit communication is possible, and we are able to derive bounds on the tradeoff between energy and spectral efficiencies. We reconfirm the curious behaviour (previously observed for non-fading MAC) of the possibility of almost perfect multi-user interference (MUI) cancellation for user densities below a critical threshold. Further, we demonstrate the suboptimality of standard solutions such as orthogonalization (i.e. TDMA/FDMA) and treating interference as noise (i.e. pseudo-random CDMA without multi-user detection). Notably, the problem treated here can be seen as a variant of support recovery in compressed sensing for the unusual definition of sparsity with one non-zero entry per each contiguous section of 2k coordinates. This identifies our problem with that of the sparse regression codes (SPARCs) and hence our results can be equivalently understood in the context of SPARCs with sections of length 2100. Finally, we discuss the relation of the almost perfect MUI cancellation property and the replica-method predictions. [ABSTRACT FROM AUTHOR]

This paper characterizes the performance in terms of queueing stability of a network composed of multiple MIMO transmitter-receiver pairs taking into account the dynamic traffic pattern and the probing/feedback cost. We adopt a centralized scheduling scheme that selects a number of active pairs in each time-slot. We consider that the transmitters apply interference alignment (IA) technique if two or more pairs are active, whereas in the special case where one pair is active point-to-point MIMO singular value decomposition (SVD) is used. We consider a time-division duplex (TDD) system where transmitters acquire their channel state information (CSI) by decoding the pilot sequences sent by the receivers. Since global CSI knowledge is required for IA, the transmitters have also to exchange their estimated CSIs over a backhaul of limited capacity (i.e. imperfect case). Under this setting, we characterize in this paper the stability region of the system under both the imperfect and perfect (i.e. unlimited backhaul) cases, then we examine the gap between these two resulting regions. Further, under each case we provide a centralized probing policy that achieves the max stability region. These stability regions and scheduling policies are given for the symmetric system, where all the path loss coefficients are equal to each other, as well as for the general system. For the symmetric system, we provide the conditions under which IA yields a queueing stability gain compared to SVD. Under the general system, the adopted scheduling policy is of a high computational complexity for moderate numbers of pairs, consequently we propose an approximate policy that has a reduced complexity but that achieves only a fraction of the system stability region. A characterization of this fraction is provided. [ABSTRACT FROM PUBLISHER]

Building on the recent coded-caching breakthrough by Maddah-Ali and Niesen, the work here considers the $K$ -user cache-aided wireless multi-antenna symmetric broadcast channel with random fading and imperfect feedback, and analyzes the throughput performance as a function of feedback statistics and cache size. In this setting, this paper identifies the optimal cache-aided degrees-of-freedom (DoF) within a factor of 4, by identifying near-optimal schemes that exploit a new synergy between coded caching and delayed CSIT, as well as by exploiting the unexplored interplay between caching and feedback-quality. The DoF expressions reveal an initial gain due to current CSIT, and an additional gain due to coded caching, which is exponential in the sense that any linear decrease in the required DoF performance, allows for an exponential reduction in the required cache size. In the end, this paper reveals three new aspects of caching: a synergy between memory and delayed feedback, a tradeoff between memory and current CSIT, and a powerful ability to provide cache-aided feedback savings. [ABSTRACT FROM PUBLISHER]

In this paper, we design energy-efficient space constellations for multiuser multi-input single-output visible light communication broadcast systems with channel state information (CSI) at the receiver in the three scenarios: 1) with CSI at the transmitter (CSIT); 2) with statistical CSIT; and 3) without CSIT. By utilizing the cooperation of multiuser interference, optimal multidimensional additively uniquely decomposable constellation groups are designed to optimize the received worst case performance metrics of all users subject to two commonly used power constraints, i.e., average and peak optical power constraints. The resulting optimal designs are proved to be pulse amplitude modulated with an optimal beamformer, which can be efficiently attained by numerical search for Scenarios 1 and 2 and be given in a closed form for Scenario 3. One of the common significant advantages of these designs is the fast demodulation of the sum signal from a noisy received signal, since these optimal designs result in an equivalent ideal scalar AWGN channel. Comprehensive computer simulations demonstrate that our designs significantly outperform traditional zero-forcing, minimum mean square error, and time-division methods. [ABSTRACT FROM AUTHOR]

This paper obtains the first degrees of freedom (DoFs) bound that is provably sensitive tonetworkcoherence time, i.e., coherence time in an interference network, where all channels experience the same coherence patterns. This is accomplished by a novel adaptation of the aligned image sets bound and settles various open problems noted previously by Naderi and Avestimehr and by Gouet al.For example, a necessary and sufficient condition is obtained for the optimality of 1/2 DoF per user in a partially connected interference network, where the channel state information at the receivers (CSIRs) is perfect, the channel state information at the transmitters (CSITs) is instantaneous but limited to finite precision, and the network coherence time is $T_{c}=1$. The surprising insight that emerges is that even with perfect CSIR and instantaneous finite precision CSIT, the network coherence time matters, i.e., it has a DoF impact. [ABSTRACT FROM AUTHOR]

The main result of this paper is that an orthogonal access scheme, such as time division multiple access achieves the all-unicast degrees of freedom (DoF) region of the topological interference management problem if and only if the network topology graph is chordal bipartite, i.e., every cycle that can contain a chord, does contain a chord. The all-unicast DoF region includes the DoF region for any arbitrary choice of a unicast message set, so e.g., the results of Maleki and Jafar on the optimality of orthogonal access for the sum-DoF of one-dimensional convex networks are recovered as a special case. The result is also established for the corresponding topological representation of the index coding problem. [ABSTRACT FROM PUBLISHER]

Impulsive noise features in many modern communication systems—ranging from wireless to molecular—and is often modeled by the $\alpha $ -stable distribution. At present, the capacity of $\alpha $ -stable noise channels is not well understood, with the exception of Cauchy noise ( $\alpha = 1$ ) with a logarithmic constraint and Gaussian noise ( $\alpha = 2$ ) with a power constraint. In this paper, we consider additive symmetric $\alpha $ -stable noise channels with $\alpha \in (1,2]$ . We derive bounds for the capacity with an absolute moment constraint. We then compare our bounds with a numerical approximation via the Blahut–Arimoto algorithm, which provides insight into the effect of noise parameters on the bounds. In particular, we find that our lower bound is in good agreement with the numerical approximation for $\alpha $ near 2. [ABSTRACT FROM AUTHOR]

Jamming attacks can significantly impact the performance of wireless communication systems. In addition to reducing the capacity, such attacks may lead to insurmountable overhead in terms of retransmissions and increased power consumption. In this paper, we consider the multiple-input single-output (MISO) broadcast channel (BC) in the presence of a jamming attack in which a subset of the receivers can be jammed at any given time. Further, countermeasures for mitigating the effects of such jamming attacks are presented. The effectiveness of these antijamming countermeasures is quantified in terms of the degrees-of-freedom (DoF) of the MISO BC under various assumptions regarding the availability of the channel state information (CSIT) and the jammer state information at the transmitter (JSIT). The main contribution of this paper is the characterization of the DoF region of the two user MISO BC under various assumptions on the availability of CSIT and JSIT. Partial extensions to the multiuser broadcast channels are also presented. [ABSTRACT FROM PUBLISHER]

For the two-user MISO broadcast channel with imperfect and delayed channel state information at the transmitter (CSIT), the work explores the tradeoff between performance on the one hand, and CSIT timeliness and accuracy on the other hand. This paper considers a broad setting where communication takes place in the presence of a random fading process, and in the presence of a feedback process that, at any point in time, may provide CSIT estimates—of some arbitrary accuracy—for any past, current or future channel realization. This feedback quality may fluctuate in time across all ranges of CSIT accuracy and timeliness, ranging from perfectly accurate and instantaneously available estimates, to delayed estimates of minimal accuracy. Under standard assumptions, the work derives the degrees-of-freedom (DoF) region, which is tight for a large range of CSIT quality. This derived DoF region concisely captures the effect of channel correlations, the accuracy of predicted, current, and delayed-CSIT, and generally captures the effect of the quality of CSIT offered at any time, about any channel. This paper also introduces novel schemes which—in the context of imperfect and delayed CSIT—employ encoding and decoding with a phase-Markov structure. The results hold for a large class of block and nonblock fading channel models, and they unify and extend many prior attempts to capture the effect of imperfect and delayed feedback. This generality also allows for consideration of novel pertinent settings, such as the new periodically evolving feedback setting, where a gradual accumulation of feedback bits progressively improves CSIT as time progresses across a finite coherence period. [ABSTRACT FROM PUBLISHER]

Cooperation is viewed as a key ingredient for interference management in wireless networks. This paper shows that cooperation has fundamental limitations. First, it is established that in systems that rely on pilot-assisted channel estimation, the spectral efficiency is upper-bounded by a quantity that does not depend on the transmit powers; in this framework, cooperation is possible only within clusters of limited size, which are subject to out-of-cluster interference whose power scales with that of the in-cluster signals. Second, an upper bound is also shown to exist if the cooperation extends to an entire (large) system operating as a single cluster; here, pilot-assisted transmission is necessarily transcended. Altogether, it is concluded that cooperation cannot in general change an interference-limited network to a noise-limited one. Consequently, the existing literature that routinely assumes that the high-power spectral efficiency scales with the log-scale transmit power provides only a partial characterization. The complete characterization proposed in this paper subdivides the high-power regime into a degree-of-freedom regime, where the scaling with the log-scale transmit power holds approximately, and a saturation regime, where the spectral efficiency hits a ceiling that is independent of the power. Using a cellular system as an example, it is demonstrated that the spectral efficiency saturates at power levels of operational relevance. [ABSTRACT FROM AUTHOR]

Efficient link scheduling in a wireless network is challenging. Typical optimal algorithms require solving an NP-hard subproblem. To meet the challenge, one stream of research focuses on finding simpler suboptimal algorithms that have low complexity but high efficiency in practice. In this paper, we study the performance guarantee of one such scheduling algorithm, the longest-queue-first (LQF) algorithm. It is known that the LQF algorithm achieves the full capacity region, \Lambda , when the interference graph satisfies the so-called local pooling condition. For a general graph G, LQF achieves (i.e., stabilizes) a part of the capacity region, \sigma ^\ast (G) \Lambda , where \sigma ^\ast (G) is the overall local pooling factor of the interference graph G and \sigma ^\ast (G) \leq 1. It has been shown later that LQF achieves a larger rate region, \Sigma ^\ast (G) \Lambda , where \Sigma ^\ast (G) is a diagonal matrix. The contribution of this paper is to describe three new achievable rate regions, which are larger than the previously known regions. In particular, the new regions include all the extreme points of the capacity region and are not convex in general. We also discover a counterintuitive phenomenon in which increasing the arrival rate may sometime help to stabilize the network. This phenomenon can be well explained using the theory developed in this paper. [ABSTRACT FROM AUTHOR]

This paper studies the capacity region when three nodes \ \mathsf 1, \mathsf 2, \mathsf 3\ communicate with each other by sending packets through unreliable wireless medium. For each time slot, with some probabilities a packet sent by node $i$ may be received by both of the other nodes $j$ and $k$ ; received only by node $j$ (or node $k$ ); or received by neither node. Interference is avoided by enforcing that at most one node can transmit in each time slot. We assume that node $i$ can always reach node $j$ , possibly with the help of the third node $k$ , for any $i \neq j$ pairs (thus the term fully connected). One notable example of this model is any CSMA-based Wi-Fi network with three nodes within the hearing range of each other. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the problem of power control in large, random wireless networks that are obtained by “erasing” a finite fraction of nodes from a regular $d$ -dimensional lattice of $N$ transmit-receive pairs. In this model, which has the important feature of a minimum distance between transmitter nodes, we find that when the network is infinite, power control is always feasible below a positive critical value of the users’ signal-to-interference-plus-noise ratio (SINR) target. Drawing on tools and ideas from statistical physics, we show how this problem can be mapped to the Anderson impurity model for diffusion in random media. In this way, by employing the so-called coherent potential approximation method, we calculate the average power in the system (and its variance) for 1-D and 2-D networks. This approach is equivalent to traditional techniques from random matrix theory and is in excellent agreement with the numerical simulations; however, it fails to predict when power control becomes infeasible. In this regard, even though infinitely large systems are always unstable beyond a critical value of the users’ SINR target, finite systems remain stable with high probability even beyond this critical SINR threshold. We calculate this probability by analyzing the density of low lying eigenvalues of an associated random Schrödinger operator, and we show that the network can exceed this critical SINR threshold by at least $ \mathop {{\mathcal O}}\nolimits ((\log N)^{-2/d})$ before undergoing a phase transition to the unstable regime. Finally, using the same techniques, we also calculate the tails of the distribution of transmit power in the system and the rate of convergence of the Foschini–Miljanic power control algorithm in the presence of random erasures. [ABSTRACT FROM PUBLISHER]

Cognitive radio methodologies have the potential to dramatically increase the throughput of wireless systems. Herein, control strategies which enable the superposition in time and frequency of primary and secondary user transmissions are explored in contrast to more traditional sensing approaches which only allow the secondary user to transmit when the primary user is idle. In this paper, the optimal transmission policy for the secondary user when the primary user adopts a retransmission-based error control scheme is investigated. The policy aims to maximize the secondary users' throughput, with a constraint on the throughput loss and failure probability of the primary user. Due to the constraint, the optimal policy is randomized, and determines how often the secondary user transmits according to the retransmission state of the packet being served by the primary user. The resulting optimal strategy of the secondary user is proven to have a unique structure. In particular, the optimal throughput is achieved by the secondary user by concentrating its transmission, and thus its interference to the primary user, in the first transmissions of a primary user packet. The rather simple framework considered in this paper highlights two fundamental aspects of cognitive networks that have not been covered so far: 1) the networking mechanisms implemented by the primary users (error control by means of retransmissions in the considered model) react to secondary users' activity; 2) if networking mechanisms are considered, then their state must be taken into account when optimizing secondary users' strategy, i.e., a strategy based on a binary active/idle perception of the primary users' state is suboptimal. [ABSTRACT FROM PUBLISHER]

Inspired by multiaccess in dense cellular systems, the paper first considers minimizing the determinant of the sum of a subset of n i.i.d. central Wishart matrices, for any given size. When n goes to infinity, the exact scaling for more general case, selecting a subset to minimize the product-determinant-sum of n i.i.d. centralWishart matrix vectors, is provided. Specifically, suppose each vector has K Wishart matrices of format GG with G of dimension Nr x Nt. Then for any subset of size nα, the K determinants, each being the sum over one of the vector elements, will have a product no less than exp{KNr(1 + 1/KNrNt)(α - α*)log n}, for all α between α* := 1/(1 + KNrNt) and 1. The paper then applies the results to study multiaccess with cross-cell collaborations in dense environment. When each cell allows multi-users to be on and decodes by treating signals from neighboring cells as noise, the maximum throughput is characterized and achieved by selecting users based on their channels. Specifically, if every cell allows same number of nodes to be on and decodes by successive interference cancellation for in-cell nodes, the maximum throughput is Nr/1+KNtNr log n bit/s/Hz/cell when n goes to infinity, where n, K, Nr, Nt are numbers of nodes per cell, neighbors per cell, receive antennas per user and transmit antennas per base station, respectively. It is also shown that time-sharing across cells achieves higher throughput, determined by the chromatic number of the interference graph. [ABSTRACT FROM AUTHOR]

Interference alignment is an effective technique for reducing interference in wireless networks. This paper proposes a generalized interference alignment and cancellation scheme for a cellular network with multiple-input multiple-output users under a Gaussian interfering broadcast channel scenario. We first focus on a three-cell network scenario to demonstrate the basic principle of how to design the transmit beamforming matrix using a non-iterative closed-form approach. We further analytically define the degree of freedom region and numerically confirm the validity of the proposed scheme. Finally, we generalize the proposed method to the $L$ -cell case and consider the impact of different antenna configurations to maintain the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this paper, we study feedback optimization problems that maximize the users' signal to interference plus noise ratio (SINR) in a two-cell multiple-input multiple-output broadcast channel. Assuming the users learn their direct and interfering channels perfectly, they can feed back this information to the base stations (BSs) over the uplink channels. The BSs then use the channel information to design their transmission scheme. Two types of feedback are considered: 1) analog and 2) digital. In the analog feedback case, the users send their unquantized and uncoded channel state information (CSI) over the uplink channels. In this context, given a user's fixed transmit power, we investigate how he/she should optimally allocate it to feed back the direct and interfering (or cross) CSI for two types of BS cooperation schemes, namely, multicell processing (MCP) and coordinated beamforming. In the digital feedback case, the direct and cross link channel vectors of each user are quantized separately, each using the random vector quantization scheme, with different size codebooks. The users then send the index of the quantization vector in the corresponding codebook to the BSs. Similar to the feedback optimization problem for the analog feedback, we investigate the optimal bit partitioning for the direct and interfering link for both types of cooperation. We focus on regularized channel inversion precoding structures and perform our analysis in the large system limit in which the number of users per cell $(K)$ and the number of antennas per BS (N)$ tend to infinity with their ratio \beta=({K}/{N}) held fixed. We show that for both types of cooperation, for some values of interfering channel gain, usually at low values, no cooperation between the BSs is preferred. This is because, for these values of cross channel gain, the channel estimates for the cross link are not accurate enough for their knowledge to contribute to improving the SINR and there is no benefit in doing BS cooperation under that condition. We also show that for the MCP scheme, unlike in the perfect CSI case, the SINR improves only when the interfering channel gain is above a certain threshold. [ABSTRACT FROM PUBLISHER]

We consider a set of transmitter-receiver pairs, or links, that share a wireless medium and address the problem of emptying backlogged queues with given initial size at the transmitters in minimum time. The problem amounts to determining activation subsets of links, and their time durations, to form a minimum-time schedule. Scheduling in wireless networks has been studied under various formulations before. In this paper, we present fundamental insights and solution characterizations that include: 1) showing that the complexity of the problem remains high for any continuous and increasing rate function; 2) formulating and proving sufficient and necessary optimality conditions of two baseline scheduling strategies that correspond to emptying the queues using one-at-a-time or all-at-once strategies; and 3) presenting and proving the tractability of the special case in which the transmission rates are functions only of the cardinality of the link activation sets. These results are independent of physical-layer system specifications and are valid for any form of rate function. We then develop an algorithmic framework for the solution to this problem. The framework encompasses exact as well as sub-optimal, but fast, scheduling algorithms, all under a unified principle design. Through computational experiments, we finally investigate the performance of several specific algorithms from this framework. [ABSTRACT FROM AUTHOR]

This paper studies the achievable secure rate per source–destination pair in wireless networks. First, a path loss model is considered, where the legitimate and eavesdropper nodes are assumed to be placed according to Poisson point processes with intensities \lambda and \lambdae, respectively. It is shown that, as long as \lambdae/\lambda=o\left((\log n)^{-2}\right), almost all of the nodes achieve a perfectly secure rate of \Omega\left(1\over\sqrtn\right) for the extended and dense network models. Therefore, under these assumptions, securing the network does not entail a loss in the per-node throughput. The achievability argument is based on a novel multihop forwarding scheme where randomization is added in every hop to ensure maximal ambiguity at the eavesdropper(s). Second, an ergodic fading model with n source–destination pairs and ne eavesdroppers is considered. Employing the ergodic interference alignment scheme with an appropriate secrecy precoding, each user is shown to achieve a constant positive secret rate for sufficiently large n. Remarkably, the scheme does not require eavesdropper CSI (only the statistical knowledge is assumed) and the secure throughput per node increases as we add more legitimate users to the network in this setting. Finally, the effect of eavesdropper collusion on the performance of the proposed schemes is characterized. [ABSTRACT FROM PUBLISHER]

Owing to the special structure of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC), the associated capacity region computation and beamforming optimization problems are typically non-convex, and thus cannot be solved directly. One feasible approach is to consider the respective dual multiple-access channel (MAC) problems, which are easier to deal with due to their convexity properties. The conventional BC-MAC duality has been established via BC-MAC signal transformation, and is applicable only for the case in which the MIMO BC is subject to a single transmit sum-power constraint. An alternative approach is based on minimax duality, which can be applied to the case of the sum-power constraint or per-antenna power constraint. In this paper, the conventional BC-MAC duality is extended to the general linear transmit covariance constraint (LTCC) case, which includes sum-power and per-antenna power constraints as special cases. The obtained general BC-MAC duality is applied to solve the capacity region computation for the MIMO BC and beamforming optimization for the multiple-input single-output (MISO) BC, respectively, with multiple LTCCs. The relationship between this new general BC-MAC duality and the minimax duality is also discussed, and it is shown that the general BC-MAC duality leads to simpler problem formulations. Moreover, the general BC-MAC duality is extended to deal with the case of nonlinear transmit covariance constraints in the MIMO BC. [ABSTRACT FROM AUTHOR]

Wireless communication is susceptible to eavesdropping attacks because of its broadcast nature. This paper illustrates how interference can be used to counter eavesdropping and assist secrecy. In particular, a wiretap channel with a helping interferer (WT-HI) is considered. Here, a transmitter sends a confidential message to its intended receiver in the presence of a passive eavesdropper and with the help of an independent interferer. The interferer, which does not know the confidential message, helps in ensuring the secrecy of the message by sending an independent signal. An achievable secrecy rate and several computable outer bounds on the secrecy capacity of the WT-HI are given for both discrete memoryless and Gaussian channels. [ABSTRACT FROM PUBLISHER]

In many wireless systems, interference is the main performance-limiting factor, and is primarily dictated by the locations of concurrent transmitters. In many earlier works, the locations of the transmitters is often modeled as a Poisson point process for analytical tractability. While analytically convenient, the PPP only accurately models networks whose nodes are placed independently and use ALOHA as the channel access protocol, which preserves the independence. Correlations between transmitter locations in non-Poisson networks, which model intelligent access protocols, makes the outage analysis extremely difficult. In this paper, we take an alternative approach and focus on an asymptotic regime where the density of interferers \eta goes to 0. We prove for general node distributions and fading statistics that the success probability \\tt P\\tt s \sim 1-\gamma \eta^{\kappa} for \eta \rightarrow 0, and provide values of \gamma and \kappa for a number of important special cases. We show that \kappa is lower bounded by 1 and upper bounded by a value that depends on the path loss exponent and the fading. This new analytical framework is then used to characterize the transmission capacity of a very general class of networks, defined as the maximum spatial density of active links given an outage constraint. [ABSTRACT FROM PUBLISHER]

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 \beta>2, it is shown that the density of users that can be supported by treating interference as noise can scale no faster than B^2/\beta as the bandwidth B grows, while the density of users can scale linearly with B under optimal decoding. [ABSTRACT FROM PUBLISHER]

Multiple-input multiple-output (MIMO) systems are being considered as one of the key enabling technologies for future wireless networks. However, the decrease in capacity due to the presence of interferers in MIMO networks is not well understood. In this paper, we develop an analytical framework to characterize the capacity of MIMO communication systems in the presence of multiple MIMO co-channel interferers and noise. We consider the situation in which transmitters have no channel state information, and all links undergo Rayleigh fading. We first generalize the determinant representation of hypergeometric functions with matrix arguments to the case when the argument matrices have eigenvalues of arbitrary multiplicity. This enables the derivation of the distribution of the eigenvalues of Gaussian quadratic forms and Wishart matrices with arbitrary correlation, with application to both single-user and multiuser MIMO systems. In particular, we derive the ergodic mutual information for MIMO systems in the presence of multiple MIMO interferers. Our analysis is valid for any number of interferers, each with arbitrary number of antennas having possibly unequal power levels. This framework, therefore, accommodates the study of distributed MIMO systems and accounts for different spatial positions of the MIMO interferers. [ABSTRACT FROM AUTHOR]

In the analysis of large random wireless networks, the underlying node distribution is almost ubiquitously assumed to be the homogeneous Poisson point process. In this paper, the node locations are assumed to form a Poisson cluster process on the plane. We derive the distributional properties of the interference and provide upper and lower bounds for its distribution. We consider the probability of successful transmission in an interference-limited channel when fading is modeled as Rayleigh. We provide a numerically integrable expression for the outage probability and closed-form upper and lower bounds. We show that when the transmitter-receiver distance is large, the success probability is greater than that of a Poisson arrangement. These results characterize the performance of the system under geographical or MAC-induced clustering. We obtain the maximum intensity of transmitting nodes for a given outage constraint, i.e., the transmission capacity (of this spatial arrangement) and show that it is equal to that of a Poisson arrangement of nodes. For the analysis, techniques from stochastic geometry are used, in particular the probability generating functional of Poisson cluster processes, the Palm characterization of Poisson cluster processes, and the Campbell-Mecke theorem. [ABSTRACT FROM AUTHOR]