A novel low-complexity wireless neighbor discovery scheme, referred to as sparse orthogonal frequency division multiplexing (sparse-OFDM) is proposed. One area of application is the "Internet of Things" (IoT). The number of devices is very large while every device accesses the network with a small probability, so the number of active devices in a frame is much smaller than the total local device population. Sparse OFDM is a one-shot transmission scheme with low complexity, which exploits both the parallel channel access offered by OFDM and the bursty nature of transmissions. When the transmission delay of each device is an integer number of symbol intervals, analysis and simulation show that sparse OFDM enables successful asynchronous neighbor discovery using a much smaller code length than random access schemes.
Recently, the idea of codes on graph has been applied in random access @cite_12 @cite_33 . One scheme is named coded slotted ALOHA, where the packets are repeatedly transmitted in different slots and are decoded using successive cancellation. These works assume synchronization transmission and perfect interference cancellation. The asynchrounous model has been studied in @cite_30 @cite_18 @cite_10 , where the asynchronicity is modeled to cause additional interference. However, perfect interference cancellation was still assumed. Rateless codes have been proposed for multiple access in machine-to-machine communications @cite_16 , where the channel gains are assumed to be known. As the number of users increases, the imperfect channel estimatioon is detrimental to the performance of successive cancellation.
@cite_30 @cite_18 @cite_33 @cite_16 @cite_10 @cite_12
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We propose a novel distributed random access scheme for wireless networks based on slotted ALOHA, motivated by the analogies between successive interference cancellation and iterative belief-propagation decoding on erasure channels. The proposed scheme assumes that each user independently accesses the wireless link in each slot with a predefined probability, resulting in a distribution of user transmissions over slots. The operation bears analogy with rateless codes, both in terms of probability distributions as well as to the fact that the ALOHA frame becomes fluid and adapted to the current contention process. Our aim is to optimize the slot access probability in order to achieve rateless-like distributions, focusing both on the maximization of the resolution probability of user transmissions and the throughput of the scheme. Future wireless access points may have to support sporadic transmissions from a massive number of unattended machines. Recently, there has been a lot of interest in the design of massive uncoordinated multiple access schemes for such systems based on clever enhancements to slotted ALOHA. A close connection has been established between the design of the multiple access scheme and the design of low density generator matrix codes. Based on this connection, optimal multiple access schemes have been designed based on slotted ALOHA and successive interference cancellation, assuming that the number of users in the network is known at the transmitters. In this paper, we extend this work and consider the design of universal uncoordinated multiple access schemes that are agnostic to the number of users in the network. We design Markov chain based transmission policies and numerical results show that substantial improvement to slotted ALOHA is possible. The rise of machine-to-machine communications has rekindled interest in random access protocols as a support for a massive number of uncoordinatedly transmitting devices. The legacy ALOHA approach is developed under a collision model, where slots containing collided packets are considered as waste. However, if the common receiver (e.g. base station) is able to store the collision slots and use them in a transmission recovery process based on successive interference cancellation, the design space for access protocols is radically expanded. We present the paradigm of coded random access, in which the structure of the access protocol can be mapped to a structure of an erasure-correcting code defined on a graph. This opens the possibility to use coding theory and tools for designing efficient random access protocols, offering markedly better performance than ALOHA. Several instances of coded random access protocols are described, as well as a case study on how to upgrade a legacy ALOHA system using the ideas of coded random access. In this paper, a random access scheme is introduced, which relies on the combination of packet erasure correcting codes and successive interference cancellation (SIC). The scheme is named coded slotted ALOHA. A bipartite graph representation of the SIC process, resembling iterative decoding of generalized low-density parity-check codes over the erasure channel, is exploited to optimize the selection probabilities of the component erasure correcting codes through a density evolution analysis. The capacity (in packets per slot) of the scheme is then analyzed in the context of the collision channel without feedback. Moreover, a capacity bound is developed, and component code distributions tightly approaching the bound are derived. We investigate the detection dynamics of a soft parallel interference canceler (soft-PIC), which includes a hard-PIC as a special case, for code-division multiple-access (CDMA) multiuser detection, applied to a randomly spread, fully synchronous base-band uncoded CDMA channel model with additive white Gaussian noise under perfect power control in the large-system limit. We analyze the detection dynamics of some iterative detectors, namely soft-PIC, the Onsager-reaction-canceling parallel interference canceler (ORC-PIC) and the belief-propagation-based detector (BP-based detector), by the generating functional analysis (GFA). The GFA allows us to study the asymptotic behavior of the dynamics in the infinitely large system without assuming the independence of messages. We study the detection dynamics and the stationary estimates of an iterative algorithm. We also show the decoupling principle in iterative multiuser detection algorithms in the large-system limit. For a generic iterative multiuser detection algorithm with binary input, it is shown that the multiuser channel is equivalent to a bank of independent single-user additive non-Gaussian channels, whose signal-to-noise ratio degrades due to both the multiple-access interference and the Onsager reaction, at each stage of the algorithm. If an algorithm cancels the Onsager reaction, the equivalent single-user channels coincide with an additive white Gaussian noise channel. We also discuss ORC-PIC and the BP-based detector. Interference between nodes is a critical impairment in mobile ad hoc networks. This paper studies the role of multiple antennas in mitigating such interference. Specifically, a network is studied in which receivers apply zero-forcing beamforming to cancel the strongest interferers. Assuming a network with Poisson-distributed transmitters and independent Rayleigh fading channels, the transmission capacity is derived, which gives the maximum number of successful transmissions per unit area. Mathematical tools from stochastic geometry are applied to obtain the asymptotic transmission capacity scaling and characterize the impact of inaccurate channel state information (CSI). It is shown that, if each node cancels interferers, the transmission capacity decreases as as the outage probability vanishes. For fixed , as grows, the transmission capacity increases as where is the path-loss exponent. Moreover, CSI inaccuracy is shown to have no effect on the transmission capacity scaling as vanishes, provided that the CSI training sequence has an appropriate length, which we derive. Numerical results suggest that canceling merely one interferer by each node may increase the transmission capacity by an order of magnitude or more, even when the CSI is imperfect. A first aspect of the invention is a method of transmitting data packets over a transmission channel shared by a plurality of users, based on the time and or frequency diversity slotted Aloha technique, in which at least two replicas of each packet to be transmitted are sent over said transmission channel, wherein each replica transports signaling information enabling the other replica(s) of the same packet to be located in the time and or frequency domain. A second aspect of the invention is a method of recovering packets in the receiver, the method exploiting said signaling information to execute an interference cancellation algorithm for recovering packets corrupted by collisions caused by access conflicts. Other aspects of the invention are a transmitter equipment and a receiver packet recovery equipment adapted to use said methods. The effect of full-duplex cooperative relaying in a random access multiuser network is investigated here. First, we model the self-interference incurred due to full-duplex operation, assuming multi-packet reception capabilities for both the relay and the destination node. Traffic at the source nodes is considered saturated and the cooperative relay, which does not have packets of its own, stores a source packet that it receives successfully in its queue when the transmission to the destination has failed. We obtain analytical expressions for key performance metrics at the relay, such as arrival and service rates, stability conditions, and average queue length, as functions of the transmission probabilities, the self interference coefficient, and the links' outage probabilities. Furthermore, we study the impact of the relay node and the self-interference coefficient on the per-user and aggregate throughput, and the average delay per packet. We show that perfect self-interference cancelation plays a crucial role when the SINR threshold is small, since it may result to worse performance in throughput and delay comparing with the half-duplex case. This is because perfect self-interference cancelation can cause an unstable queue at the relay under some conditions. The transmission capacity (TC) of a wireless ad hoc network is defined as the maximum spatial intensity of successful transmissions such that the outage probability does not exceed some specified threshold. This work studies the improvement in TC obtainable with successive interference cancellation (SIC), an important receiver technique that has been shown to achieve the capacity of several classes of multiuser channels, but has not been carefully evaluated in the context of ad hoc wireless networks. This paper develops closed-form upper bounds and easily computable lower bounds for the TC of ad hoc networks with SIC receivers, for both perfect and imperfect SIC. The analysis applies to any multiuser receiver that cancels the K strongest interfering signals by a factor z isin [0, 1]. In addition to providing the first closed-form capacity results for SIC in ad hoc networks, design-relevant insights are made possible. In particular, it is shown that SIC should be used with direct sequence spread spectrum. Also, any imperfections in the interference cancellation rapidly degrade its usefulness. More encouragingly, only a few - often just one - interfering nodes need to be canceled in order to get the vast majority of the available performance gain. In this paper a new multiple access scheme dubbed contention resolution diversity slotted ALOHA (CRDSA) is introduced and its performance and implementation are thoroughly analyzed. The scheme combines diversity transmission of data bursts with efficient interference cancellation techniques. It is shown that CRDSA largely outperforms the classical lotted ALOHA (SA) technique in terms of throughput under equal packet loss ratio conditions (e.g. 17-fold improvement at packet loss ratio = 2 middot 10-2). CRDSA allows to boost the performance of random access (RA) channels in the return link of interactive satellite networks, making RA very efficient and providing low latency for the transmission of small size sparse packets. Implementation-wise it is shown that the CRDSA technique can be easily integrated in systems equipped with digital burst demodulators. In this paper we consider a simple cooperative network consisting of a source, a destination and a cluster of decode-and-forward relays characterized by the half-duplex constraint. At each time-slot the source and (possibly) one of the relays transmit a packet to another relay and the destination, respectively. When the source and a relay transmit simultaneously, inter-relay interference is introduced at the receiving relay. In this work, with the aid of buffers at the relays, we mitigate the detrimental effect of inter-relay interference through either interference cancellation or mitigation. More specifically, we propose the min-power opportunistic relaying protocol that minimizes the total energy expenditure per time slot under an inter-relay interference cancellation scheme. The min-power relay-pair selection scheme, apart from minimizing the energy expenditure, also provides better throughput and lower outage probability than existing works in the literature. The performance of the proposed scheme is demonstrated via illustrative examples and simulations in terms of outage probability and average throughput. The transmission capacity of an ad-hoc network is the maximum density of active transmitters per unit area, given an outage constraint at each receiver for a fixed rate of transmission. Assuming that the transmitter locations are distributed as a Poisson point process, this paper derives upper and lower bounds on the transmission capacity of an ad-hoc network when each node is equipped with multiple antennas. The transmitter either uses eigen multi-mode beamforming or a subset of its antennas without channel information to transmit multiple data streams, while the receiver uses partial zero forcing to cancel certain interferers using some of its spatial receive degrees of freedom (SRDOF). The receiver either cancels the nearest interferers or those interferers that maximize the post-cancellation signal-to-interference ratio. Using the obtained bounds, the optimal number of data streams to transmit, and the optimal SRDOF to use for interference cancellation are derived that provide the best scaling of the transmission capacity with the number of antennas. With beamforming, single data stream transmission together with using all but one SRDOF for interference cancellation is optimal, while without beamforming, single data stream transmission together with using a fraction of the total SRDOF for interference cancellation is optimal. The problems of channel estimation and multiuser detection for direct sequence code division multiple access (DS CDMA) systems employing long spreading codes are considered. With regard to channel estimation, several procedures are proposed based on the least-squares approach, relying on the transmission of known training symbols but not requiring any timing synchronization. In particular, algorithms suited for the forward and reverse links of a single-rate DS CDMA cellular system are developed, and the case of a multirate multicode system, wherein high-rate users are split into multiple virtual low-rate users, is also considered. All of the proposed procedures are recursively implementable with a computational complexity that is quadratic in the processing gain, with regard to the issue of multiuser detection, an adaptive serial interference cancellation (SIC) receiver is considered, where the adaptivity stems from the fact that it is built upon the channel estimates provided by the estimation algorithm. Simulation results show that coupling the proposed estimation algorithms with a SIC receiver may yield, with a much lower computational complexity, performance levels close to those of the ideal linear minimum mean square error (MMSE) receiver, which assumes perfect knowledge of the channels for all of the users and which (in a long-code scenario) has a computational complexity per symbol interval proportional to the third power of the processing gain. We introduce a framework to study slotted Aloha with cooperative base stations. Assuming a geographic-proximity communication model, we propose several decoding algorithms with different degrees of base stations' cooperation (non-cooperative, spatial, temporal, and spatio-temporal). With spatial cooperation, neighboring base stations inform each other whenever they collect a user within their coverage overlap; temporal cooperation corresponds to (temporal) successive interference cancellation done locally at each station. We analyze the four decoding algorithms and establish several fundamental results. With all algorithms, the peak throughput (average number of decoded users per slot, across all base stations) increases linearly with the number of base stations. Further, temporal and spatio-temporal cooperations exhibit a threshold behavior with respect to the normalized load (number of users per station, per slot). There exists a positive load @math , such that, below @math , the decoding probability is asymptotically maximal possible, equal the probability that a user is heard by at least one base station; with non-cooperative decoding and spatial cooperation, we show that @math is zero. Finally, with spatio-temporal cooperation, we optimize the degree distribution according to which users transmit their packet replicas; the optimum is in general very different from the corresponding optimal distribution of the single-base station system. We consider a state-dependent three-terminal full-duplex relay channel with the channel states noncausally available at only the source, that is, neither at the relay nor at the destination. This model has application to cooperation over certain wireless channels with asymmetric cognition capabilities and cognitive interference relay channels. We establish lower bounds on the channel capacity for both discrete memoryless (DM) and Gaussian cases. For the DM case, the coding scheme for the lower bound uses techniques of rate-splitting at the source, decode-and-forward (DF) relaying, and a Gel'fand-Pinsker-like binning scheme. In this coding scheme, the relay decodes only partially the information sent by the source. Due to the rate-splitting, this lower bound is better than the one obtained by assuming that the relay decodes all the information from the source, that is, full-DF. For the Gaussian case, we consider channel models in which each of the relay node and the destination node experiences on its link an additive Gaussian outside interference. We first focus on the case in which the links to the relay and to the destination are corrupted by the same interference; and then we focus on the case of independent interferences. We also discuss a model with correlated interferences. For each of the first two models, we establish a lower bound on the channel capacity. The coding schemes for the lower bounds use techniques of dirty paper coding or carbon copying onto dirty paper, interference reduction at the source and decode-and-forward relaying. The results reveal that, by opposition to carbon copying onto dirty paper and its root Costa's initial dirty paper coding (DPC), it may be beneficial in our setup that the informed source uses a part of its power to partially cancel the effect of the interference so that the uninformed relay benefits from this cancellation, and so the source benefits in turn. At present, operators address the explosive growth of mobile data demand by densification of the cellular network so as to reduce the transmitter-receiver distance and to achieve higher spectral efficiency. Due to such network densification and the intense proliferation of wireless devices, modern wireless networks are interference-limited, which motivates the use of interference mitigation and coordination techniques. In this work, we develop a statistical framework to evaluate the performance of multi-tier heterogeneous networks with successive interference cancellation (SIC) capabilities, accounting for the computational complexity of the cancellation scheme and relevant network related parameters such as random location of the access points (APs) and mobile users, and the characteristics of the wireless propagation channel. We explicitly model the consecutive events of canceling interferers and we derive the success probability to cancel the n-th strongest signal and to decode the signal of interest after n cancellations. When users are connected to the AP which provides the maximum average received signal power, the analysis indicates that the performance gains of SIC diminish quickly with n and the benefits are modest for realistic values of the signal-to-interference ratio (SIR). We extend the statistical model to include several association policies where distinct gains of SIC are expected: (i) minimum load association, (ii) maxi- mum instantaneous SIR association, and (iii) range expansion. Numerical results show the effectiveness of SIC for the considered association policies. This work deepens the understanding of SIC by defining the achievable gains for different association policies in multi-tier heterogeneous networks. The transmission capacity of an ad-hoc network is the maximum density of active transmitters in an unit area, given an outage constraint at each receiver for a fixed rate of transmission. Assuming channel state information is available at the receiver, this paper presents bounds on the transmission capacity as a function of the number of antennas used for transmission, and the spatial receive degrees of freedom used for interference cancelation at the receiver. Canceling the strongest interferers, using a single antenna for transmission together with using all but one spatial receive degrees of freedom for interference cancelation is shown to maximize the transmission capacity. Canceling the closest interferers, using a single antenna for transmission together with using a fraction of the total spatial receive degrees of freedom for interference cancelation depending on the path loss exponent, is shown to maximize the transmission capacity. Integer-forcing receivers generalize traditional linear receivers for the multiple-input multiple-output channel by decoding integer-linear combinations of the transmitted streams, rather then the streams themselves. Previous works have shown that the additional degree of freedom in choosing the integer coefficients enables this receiver to approach the performance of maximum-likelihood decoding in various scenarios. Nonetheless, even for the optimal choice of integer coefficients, the additive noise at the equalizer's output is still correlated. In this work we study a variant of integer-forcing, termed successive integer-forcing, that exploits these noise correlations to improve performance. This scheme is the integer-forcing counterpart of successive interference cancellation for traditional linear receivers. Similarly to the latter, we show that successive integer-forcing is capacity achieving when it is possible to optimize the rate allocation to the different streams. In comparison to standard successive interference cancellation receivers, the successive integer-forcing receiver offers more possibilities for capacity achieving rate tuples, and in particular, ones that are more balanced. Asynchronous random access (RA) protocols are particularly attractive for their simplicity and avoidance of tight synchronization requirements. Recent enhancements have shown that the use of successive interference cancellation (SIC) can largely boost the performance of these schemes. A further step forward in the performance can be attained when diversity combining techniques are applied. In order to enable combining, the detection and association of the packets to their transmitters has to be done prior to decoding. We present a solution to this problem, that articulates into two phases. Non-coherent soft-correlation as well as interference-aware soft-correlation are used for packet detection. We evaluate the detection capabilities of both solutions via numerical simulations. We also evaluate numerically the spectral efficiency achieved by the proposed approach, highlighting its benefits. A (layered) broadcast approach is studied for fading wiretap channels. The basic idea is to employ superposition coding to encode information into a number of layers and use stochastic encoding for each layer to keep the corresponding information secret from an eavesdropper. The legitimate receiver successively decodes information one layer after another by canceling the interference caused by the layers that the receiver has already decoded. The advantage of this approach is that the transmitter does not need to know the channel states to the legitimate receiver and the eavesdropper, but can still securely transmit certain layers of information to the legitimate receiver. The layers that can be securely transmitted are determined by the channel states to the legitimate receiver and the eavesdropper. The Gaussian wiretap channel with fixed channel gains is first studied to illustrate the idea of the broadcast approach. Three cases of block fading wiretap channels with a stringent delay constraint are then studied, in which either the legitimate receiver's channel, the eavesdropper's channel, or both channels are fading. For each case, the secrecy rate that can be achieved by using the broadcast approach is obtained, and the optimal power allocation over the layers (or the conditions on the optimal power allocation) is also derived.