The usual approach to mitigate multiple access interference (MAI) in the uplink of cellular OFDMA based systems is to use relatively large cyclic prefixes as time domain guard periods. In this paper, we suggest to use a combination of short time domain guard periods and frequency domain guard bands to protect against MAI instead. Guard bands can be added and removed as necessary and, thus, increase the MAI protection flexibility. We show that, if optimally applied, the use of guard bands can significantly increase the system’s uplink capacity or minimum capacity per user.
The simulation models of wireless networks rapidly increase in complexity to accurately model wireless channel characteristics and the properties of advanced transmission technologies. Such detailed models typically lead to a high computational load per simulation event that accumulates to extensive simulation runtimes. Reducing runtimes through parallelization is challenging since it depends on detecting causally independent events that can execute concurrently. Most existing approaches base this detection on lookaheads derived from channel propagation latency or protocol characteristics. In wireless networks, these lookaheads are typically short, causing the potential for parallelization and the achievable speedup to remain small. This paper presents Horizon, which unlocks a substantial portion of a simulation model's workload for parallelization by going beyond the traditional lookahead. We show how to augment discrete events with durations to identify a much larger horizon of independent simulation events and efficiently schedule them on multi-core systems. Our evaluation shows that this approach can significantly cut down the runtime of simulations, in particular for complex and accurate models of wireless networks.
This paper presents a performance model for dynamic resource allocation in cellular deployments of IEEE 802.16e-like systems. More specifically, we derive a framework which allows to quantify the number of VoIP calls that can be supported in downlink of such systems purely based on the average SINR per terminal. The major difficulty to overcome is to predict the impact of dynamic resource allocations on the system performance in the presence of interference. We show that dynamic resource allocations perform a transformation of subcarrier SINR PDFs and derive an approximate, closed-form representation of these SINR PDFs. Based on these derivations, we derive rate PMFs which predicts system performance up to a gap of about 25% compared to optimal system performance. Furthermore, the model allows for detailed investigation of dynamic resource allocation in interference-limited scenarios. We show that the average SINR is not a valid metric to predict system performance from, but instead the received power of the signal of interest is much more important (together with the received interference power). To the best of our knowledge, such performance models are novel while the presented insights have significant consequences for network design and network self-optimization.
This paper presents a performance model for dynamic resource allocation in interference-limited OFDMA-based cellular networks. Specifically, we derive an analytical framework by which it is possible to estimate the VoIP capacity of the cell per downlink frame, purely based on the average SINR per terminal. Hence, this framework can be used for admission control. The major difficulty to overcome is to predict the impact of dynamic resource allocations on the system performance in the presence of multiple interfering cells. We show that dynamic resource allocations transform the distribution of subcarrier SINR and derive an approximate, closed-form representation of these transformed distributions. Based on these derivations, we obtain rate probability mass functions per terminal which predict system performance up to a gap of about 26 % compared to optimal system performance.
The problem of transmitting a remote source via multiple agents to a single destination is considered with secrecy constraints. In particular, noisy versions of a source are observed by multiple agents who then encode and transmit their observations to a decoder over dedicated noisy channel. The decoder should be able to reconstruct the remote source within a certain distortion limit. In addition, there exists an eavesdropper with correlated side information to the source who is capable of wiretapping the links from the agents to the decoder so as to extract as much information as possible about the source. Therefore, the agents should encode their observations in such a way that while as less information as possible is leaked to the eavesdropper the decoder can satisfy the distortion constraint. For this problem, we study the tradeoffs among agents' transmission rates, experienced distortion at the destination, and equivocation rates at the eavesdropper, and provide an achievable region.
We study a lossy source coding problem with secrecy constraints in which a remote information source should be transmitted to a single destination via multiple agents in the presence of a passive eavesdropper. The agents observe noisy versions of the source and independently encode and transmit their observations to the destination via noiseless rate-limited links. The destination should estimate the remote source based on the information received from the agents within a certain mean distortion threshold. The eavesdropper, with access to side information correlated to the source, is able to listen in on one of the links from the agents to the destination in order to obtain as much information as possible about the source. This problem can be viewed as the so-called CEO problem with additional secrecy constraints. We establish inner and outer bounds on the ratedistortion- equivocation region of this problem. We also obtain the region in special cases where the bounds are tight. Furthermore, we study the quadratic Gaussian case and provide the optimal rate-distortion-equivocation region when the eavesdropper has no side information and an achievable region for a more general setup with side information at the eavesdropper.
A lossy source coding problem with secrecy constraints is considered where a remote information source should be transmitted to a single destination via multiple agents in the presence of an eavesdropper. The agents observe noisy versions of the source and independently encode and transmit their observations to the destination via noiseless rate-limited links. Unbeknownst to the agents, an eavesdropper intercepts one of the links from the agents to the destination to learn as much as possible about the source. The destination should estimate the remote source subject to a mean distortion threshold. This problem can be viewed as the CEO problem with addition of secrecy constraints. We establish inner and outer bounds on the rate-distortion-equivocation region. In addition, we provide the optimal rate-distortion-equivocation region for the quadratic Gaussian case when the eavesdropper has no side information.
In this paper, we investigate the problem of transmitting a remote information source to a single destination via multiple agents in the presence of an eavesdropper. The agents observe noisy versions of the source, then, compress and transmit their observations to the destination via noiseless rate-limited links. The destination should reconstruct the remote source based on the information received from the agents. The eavesdropper, with access to side information correlated with the source, can eavesdrop one of the links from the agents to the destination to obtain as much information as possible about the source. For this problem, we determine the rates at which the agents should transmit such that the destination can recover the source while the equivocation at the eavesdropper node is maximized. We derive inner and outer bounds on the compression-equivocation region. Furthermore, we obtain the compression-equivocation region in special cases where the bounds are tight.
In this paper, we investigate the performance of the wiretap Rayleigh fading channel in the presence of statistical delay constraints. We invoke tools from stochastic network calculus to derive probabilistic bounds on the delay. This method requires a statistical characterization of the wiretap fading service process, which we derive in closed form. We then validate these analytical bounds via simulations. Interestingly, the analysis of the wiretap fading channel reveals close structural similarities with the interference channel in terms of service process characterization, which is derived in our prior work. In our numerical evaluations, we show that the delay performance of the wiretap fading channel is in particular sensitive to bursty arrival processes due to the high variance of the service process.
We consider the problem of code design for compression of correlated sources under adversarial attacks. A scenario with three correlated sources is considered in which at most one source is compromised by an adversary. The theoretical minimum achievable sum-rate for this scenario was derived by Kosut and Tong. We design layered LDPC convolutional codes for this problem, assuming that one of the sources is available at the common decoder as side information. We demonstrate that layered LDPC convolutional codes constitute a sequence of nested codes where each sub-code is capacity-achieving for the binary symmetric channels used to model the correlation between sources, and therefore, can ideally achieve the theoretical minimum sum-rate. Simulated performance results for moderate block length show a small gap to the theoretical limit, and as the block length increases the gap vanishes.
In this paper we consider the design of semi-static inter-cell interference coordination schemes for LTE networks. In this approach, base stations coordinate the power settings per resource block over long time spans such as seconds. In order to optimize the power settings, one needs to employ models which predict the rate of terminals over the next coordination period under the usage of a given power setting. However, these models are typically quite simple and neglect the impact from fading as well as from dynamic resource allocation performed at the base stations on a millisecond basis. Ignoring such properties of OFDMA networks leads therefore to suboptimal transmit power settings. In this paper, we study the impact from a precise rate prediction model that accurately accounts for fading and dynamic resource allocation. On the down-side, this more precise model leads to a much more involved optimization problem to be solved once per coordination period. We propose two different heuristic methods to deal with this problem. Especially the usage of genetic algorithm results to be promising to counteract the complexity increase. We then study the overall system performance and find precise rate prediction models to be essential for semi-static interference coordination as they provide significant performance improvements in comparison to approaches with simpler models.
A deep understanding of the queuing performance of wireless networks is essential for the advancement of future wireless communications. The stochastic nature of wireless channels in general gives rise to a time varying transmission rate. In such an environment, interference is increasingly becoming a key constraint. Obtaining an expressive model for offered service of such channels has major implications in the design and optimization of future networks. However, interference channels are not well-understood with respect to their higher layer performance. The particular difficulty for handling interference channels arises from the superposition of random fading processes for the signals of the transmitters involved (i.e., for the signal of interest and for the signals of the interferers). Starting from the distribution of the signal-to-interference-plus-noise ratio (SINR), we derive a statistical characterization of the underlying service process in terms of its Mellin transform. Then, we adapt a recent stochastic network calculus approach for fading channels to derive measures of the queuing performance of single-and multi-hop wireless interference networks. Special cases of our solution include noise-limited and interference-limited systems. A key finding of our analysis is that for a given average signal and average sum interference power, the performance of interfered systems not only depends on the relative strength of the sum interference with respect to the signal-of-interest power, but also on the interference structure (i.e., the number of interferers) as well as the absolute levels.