We consider the optimization of a network with amplify-and-forward relays. Observing that the power limit at each relay presents a non-linear transfer function, we focus on the similarity between relay networks and neural networks. Thus, we treat relays as neurons, and use deep learning tools to achieve better optimization of the network. Deep learning optimization allows relays to exploit their non-linear regime (and hence increase their transmission power) while still avoiding harmful distortion. Moreover, copying the computational capabilities of neural networks, we can take advantage of the non-linearities and implement parts of the received functionalities over the relay network. By treating each relay element as a node in a deep neural network, our optimization results in huge gains over traditional relay optimization, and also allows the use of simpler receivers.

Widespread deployment of relays can yield a significant boost in the throughput of forthcoming wireless networks. However, the optimal operation of large relay networks is still infeasible. This paper presents two approaches for the optimization of large relay networks. In the traditional approach, we formulate and solve an optimization problem where the relays are considered linear. In the second approach, we take an entirely new direction and consider the true non-linear nature of the relays. Using the similarity to neural networks, we leverage deep-learning methodology. Unlike previous applications of neural networks in wireless communications, where neural networks are added to the network to perform computational tasks, our deep relay optimization treats the relay network itself as a neural network. By exploiting the non-linear transfer function exhibited by each relay, we achieve over 15dB gain compared to traditional optimization methods. Moreover, we are able to implement part of the network functionality over the relay network. Our findings shed light on the potential of deep relay optimization, promising significant advancements in future wireless communication systems.

We present a novel power-efficient and low-complexity scheme for cache-aided communication in networks with a multi-antenna base station that serves multiple single-antenna users. The scheme is based on transmitting coded messages to disjoint groups of users simultaneously and achieves an important trade-off between performance and complexity. The subpacketization level of the proposed scheme is sub-optimum compared to the state-of-the-art but is still feasible for a practical range of network parameters. On the other hand, the scheme achieves near-optimal performance and asymptotically achieves the same degrees of freedom (DoF) as the best-known schemes achieve. However, compared to other optimum achievable rates, the proposed scheme suffers from minor performance degradation due to power loss, which becomes negligible as the signal-to-noise ratio or the number of users grows. In return, the reductions in complexity and subpacketization allow for practical implementation of this scheme even for a large number of users. The presented scheme is also very flexible to the variation of the network topology and can easily be generalized to heterogeneous and dynamic scenarios.

We present a novel low complexity scheme for cache aided communication, where a multi-antenna base station serves multiple single-antenna mobiles. The scheme is based on transmission of coded messages to disjoint groups of users simultaneously. Compared to the state-of-the-art, the proposed scheme significantly reduces the transmission and decoding complexity. Furthermore, it substantially relaxes the subpacketization level, and involves a transmission of much smaller number of packets in each time block. The proposed scheme achieves the same degrees of freedom (DoF) as the best known scheme, but, it suffers from a performance degradation of about 1.5dB due to a loss of diversity. Nevertheless, the loss is acceptable as the reduction in complexity allows a practical implementation of this scheme even for a large number of users.

We analyze the performance of a network of very simple nano-devices that cooperate to detect and/or amplify the presence of target molecules. The nano-devices only have the capability to detect a single type of molecules and in response release molecules. Furthermore, each device has a binary operation, and releases all of its stored molecules in response to a single detection. Nevertheless, the network establishes a complex behavior through cooperation between the devices (without additional device complexity). Analysis reveals that depending on the network parameters, the network can implement a mass amplifier (that releases an amount of molecules that is proportional to the input mass) or a binary detector (that generates a macro level response to the presence of a small mass of target molecules). We characterize the network behavior and derive exact expressions for the variance of the response and the miss-detection probability.

We derive and study a novel lower bound on the performance of a partial zero forcing (PZF) receiver in the uplink of a cellular network, where the mobile locations are modeled as a homogeneous Poisson Point Process (HPPP). The PZF is a suboptimal receiver. Yet, it is easy to analyze and in many cases is close to optimal. Furthermore, the analysis of the PZF gives more insight on the behavior of the network than the optimal MMSE receiver (for example, we study the optimal distance within which interference should be suppressed). Unlike the existing analysis for the optimal MMSE receiver, our novel bound holds also in the presence of thermal noise and for finite number of antennas. This bound is easy to evaluate and proved to be asymptotically tight. Comparing to the asymptotic result for MMSE, we also give the exact SINR loss of PZF compared to MMSE.

We study the problem of cache-aided communication for cellular networks with multi-user and multiple antennas at finite signal-to-noise ratio. Users are assumed to have non-symmetric links, modeled by wideband fading channels. We show that the problem can be formulated as a linear program, whose solution provides a joint cache allocation along with pre-fetching and fetching schemes that minimize the duration of the communication in the delivery phase. The suggested scheme uses zero-forcing and cached interference subtraction, and hence, allows each user to be served at the rate of its own channel. Thus, this scheme is better than the previously published schemes that are compromised by the poorest user in the communication group. We also consider a special case of the parameters for which we can derive a closed form solution and formulate the optimal power, rate, and cache optimization. This special case shows that the gain of MIMO coded caching goes beyond the throughput. In particular, it is shown that in this case, the cache is used to balance the users such that fairness and throughput are no longer contradicting. More specifically, in this case, strict fairness is achieved jointly with maximizing the network throughput.

We consider a user-centric co-operative cellular network, where base stations (BSs) close to a mobile co-operate to detect its signal using a (joint) linear minimum-mean-square-error receiver. The BSs are at arbitrary positions and mobiles are modeled as a planar Poisson point process (PPP). Combining stochastic geometry and infinite-random-matrix theory, we derive a simple expression for the spectral efficiency of this complex system as the number of antennas grows large. This framework is applied to BS locations from PPPs and hexagonal grids and is validated through Monte Carlo simulations. The results reveal the influence of tangible system parameters, such as mobile and BS densities, number of antennas per BS, and number of co-operating BSs on achievable spectral efficiencies. Among other insights, we find that for a given BS density and a constraint on the total number of co-operating antennas, all co-operating antennas should be located at a single BS. On the other hand, in our asymptotic regime, for the same number of co-operating antennas, if the network is limited by the area density of antennas, then the number of co-operating BSs should be increased with a fewer antennas per BS.

In this paper, we consider routing in random wireless-ad hoc-networks, where each node is equipped with a single antenna. Our analysis uses a proper model of the physical layer together with an abstraction of higher communication layers. We assume that the nodes are distributed according to a Poisson-point-process and consider routing schemes that select the next relay based on the geographical locations, the channel gains of its neighbor nodes and the statistical characterization of all other nodes. While many routing problems are formulated as optimization problems, the optimal distributed solution is rarely accessible. In this paper, we present the exact optimal solution for the scenario analyzed. The optimal routing is given as a maximization of a routing metric, which depends solely on the known partial channel state information and includes an expectation with respect to the interference statistics. The optimal routing scheme is important because it gives an upper bound on the performance of any other routing scheme. We also present sub-optimal routing schemes that only use part of the available knowledge and require much lower computational complexity. Numerical results demonstrate that the performance of the low complexity schemes is close to optimal and outperforms other tested routing schemes.

We derive a closed-form expression for the throughput in the uplink of a cooperative massive MIMO system. We consider a network where a cluster of base stations co-operate to detect signals from mobiles using a linear minimum-mean-square error receiver. A user-centric clustering approach is assumed, where the cluster that detects the signals from each mobile is composed of the K base stations that are closest to the mobile. The analysis combines stochastic geometry and infinite random matrix theory. We assume that base stations and mobiles are distributed as independent Poisson Point Processes on the plane. Using an asymptotic analysis, a closed-form expression for the spectral efficiency is derived, which is verified by simulations to be accurate even for a moderate number of antennas. This result helps us understand the influence of tangible system parameters such as mobile and base-station densities, number of antennas per base station, and number of co-operating base stations on spectral efficiencies. Our findings show that for a given number of cooperating antennas, it is optimal to have all cooperating antennas in a single base station. But, if the area density of antennas is also limited, then the number of co-operating base stations should be increased instead.

The performance of random wireless ad-hoc networks (WANETs) is primarily limited by their self-interference. The utilization of a decentralized carrier sensing multiple access (CSMA) protocol protects the participating receivers from the presence of strong interferers and enhances the performance compared to the simpler ALOHA protocol. In this work, we analyze the ergodic rate density (ERD) of slotted and unslotted CSMA WANETs in the small backoff probability regime. Our main result is the derivation of simple expressions, which describe the ERD of CSMA WANETs as a function of the backoff probability, the path-loss exponent, and the ERD of the same WANET when applying the ALOHA protocol. The ERD expressions for both the slotted and the unslotted variants are shown to grow with the back-off probability. For the slotted variant the gain of CSMA over ALOHA is equal to the backoff probability. On the other hand, for the unslotted variant this gain is smaller by a constant factor, which is within the range of 0.57 to 0.67 for all cases of practical interest. Simulation results validate the precision of the derived expressions and demonstrate their capability to predict the optimal system parameters with very good accuracy.

We present a novel upper bound on the Ergodic Rate Density (ERD) of ALOHA wireless ad-hoc networks. Our analysis uses a proper model of the physical layer together with an abstraction of higher communication layers. The novel bound is very general and supports various system models including for example, beamforming, spatial multiplexing, different fading models and different power control schemes. We also derive a closed form expression for the maximal gap between the novel bound and a known lower bound on the ERD. This maximal gap holds for any network that operates below the optimal density. This expression is simple to evaluate and only depends on the path loss factor. For example, for a path loss factor of α = 3 the novel upper bound is proved to be at most 31% higher than the lower bound (and hence also from the actual ERD). The usefulness and the generality of the novel bound is demonstrated by applications in multiple-antenna schemes. In particular, we study the optimization of the number of transmitted spatial streams in a MIMO network and derive the scaling of the ERD as the number of antennas grows. The results are further demonstrated using extensive simulations.

In this paper, we study the performance of rateless error correction codes in a wireless ad hoc network (WANET). The salient features of a WANET are Rayleigh fading, constant power transmission, pure ALOHA as the channel access protocol, and the nodes being modeled by a homogeneous space-time Poisson point process. For such a WANET, this paper quantifies the rate density (RD) and the dynamic variations of the packet transmission time by deriving an upper bound on the CCDF of the packet transmission time. The performance of rateless codes is compared with two benchmarks, i.e., the ergodic RD (ERD) and the RD of fixed-rate codes. The proposed rateless coding scheme does not require time diversity as each packet is transmitted within a single coherence time. Yet, it is shown that the RD can be up to 76% and 50% of the ERD in noise- and interference-limited regimes, respectively. Thus, the presented network nearly achieves the ERD while requiring significantly shorter delays. This paper shows that a low-complexity Gaussian receiver with a nearest neighbor decoder has almost the performance of an ideal matched receiver. We also show that power control in the form of channel thresholding leads to a 72% gain in the RD relative to a constant power transmission.

The performance of Wireless Ad hoc Networks (WANETs) depends on the availability of Channel State Information (CSI) on all channels in the network. In this work we study the performance when each receiver has CSI only on the channel from its desired transmitter. We present a novel lower bound on the Ergodic Rate Density of a WANET with partial CSI. The novel bound is compared to a previously known bound and its superiority is demonstrated. We also use the novel bound to study the effect of CSI availability on the WANETs' performance. We show that for Rayleigh fading the CSI-gain of the bound can be up to 78%. But, if each network is optimized with respect to the active transmitter density, then the CSI gain of the bound is at most 13%. Simulation results show the practicality of the novel bound and the accuracy of the CSI-gain expressions.

In this paper, we propose a new method for inter-carrier interference (ICI) mitigation in orthogonal frequency-division multiplexing (OFDM) systems. The proposed approach views the signal reconstruction problem at the receiver end as an integer least squares (ILS) problem, and uses a recently developed spectral approach called sequential probabilistic ILS (SPILS) to solve it. The proposed approach outperforms other state-of-the-art approaches while having the same computational complexity. In addition, we present a novel extension to the SPILS scheme that allows the generation of soft decisions (for communication systems which use soft-decision decoding). The use of soft-decision decoding (naturally) brings significant improvement in the detection reliability, and we show that the proposed method again outperforms other state-of-the-art approaches. To better address the tradeoff between performance and complexity, we first suggest a novel method to reduce the number of matrix inversions required and hence, to reduce the implementation complexity without any degradation in performance. We also introduce a novel low complexity scheme termed Quick SPILS (QSPILS) in which we lose a little in detection reliability, but significantly reduce the implementation complexity.

In this paper, we propose and analyze a low-complexity precoding scheme for cognitive radio networks. We consider a secondary user, equipped with multiple transmit antennas, that is allowed to access the spectrum of the primary network only if it does not interfere to the reception of the primary users. The proposed precoder is based on the signal to leakage plus noise ratio (SLNR) criterion, with additional scaling to comply with the cognitive constraint. The proposed Scaled SLNR (SSLNR) scheme is attractive for practical cognitive wireless networks as it combines near optimal performance with low implementation complexity. The SSLNR parameter is optimized using stochastic geometry analysis of an alternative gated zero-forcing scheme. The optimal parameter value is shown to depend only on the system parameters and not on the primary network density. Simulations results demonstrate the accuracy of the optimization, and show that the performance of the resulting SSLNR scheme is close to the performance of the optimal solution.

DSL systems use multi-channel processing to mitigate the electromagnetic coupling between the wires in a binder and provide high data rates to multiple users. In recent years, most multichannel processing for DSL had focused on zero-forcing (ZF) processing that was proven to be near optimal. This near optimality has been observed in numerical evaluations as well as in real life systems. However, this near optimality has only been demonstrated theoretically by relatively loose bounds. In this paper we prove novel bounds on the performance of ZF processing in DSL systems. These bounds are simpler and yet tighter than currently known bounds. These novel bounds support previously published results, and further confirm the near optimality of ZF processing.

In recent years, much attention has been paid to the analysis of random wireless ad hoc networks (WANETs) that combine the effect of the physical layer and the medium access layer. However, most works have concentrated on an outage rate model which does not accurately describe the performance of modern communication systems. In this work we consider the ergodic rate density (ERD) of a random ALOHA WANET with a homogenous Poisson point process node distribution. We present two novel lower bounds on the ERD, one for general transmission and reception strategies and the other for receivers with a spatial interference cancellation capability. The bounds are simpler than previously published results for ALOHA WANETs (that have primarily considered the outage rate density). In addition, the bounds and the bounding technique are quite general and enable the derivation of closed form expressions of the ERD for various network models. The efficiency and simplicity of the bounds are demonstrated through several applications, and insights are drawn on the behavior of the network performance as function of the path-loss factor, transmission strategies and number of antennas. Simulation results demonstrate that these simple lower bounds predict the performance of ALOHA WANETs with high accuracy.

The analysis of the channel capacity in the absence of prior channel knowledge (noncoherent channel) has gained increasing interest in recent years. Yet, the noncoherent channel capacity is still unknown for the general case. In this paper, we derive bounds on the capacity of the noncoherent, underspread complex Gaussian, orthogonal frequency division multiplexing, wide sense stationary channel with uncorrelated scattering, under a peak power constraint or a constraint on the second and fourth moments of the transmitted signal. These bounds are characterized only by the system signal-to-noise ratio (SNR) and by a newly defined quantity termed effective coherence time. Intuitively, the effective coherence time can be interpreted as the length of a block in the block-fading model in which a system with the same SNR will achieve the same capacity as in the analyzed channel. Unlike commonly used coherence time definitions, it is shown that the effective coherence time depends on the SNR, and is a nonincreasing function of it. We show that for low SNR, the capacity is proportional to the effective coherence time, while for higher SNR, the coherent channel capacity can be achieved provided that the effective coherence time is large enough.

The performance of wireless ad-hoc networks (WANET) is mainly limited by its self-interference. This interference can be mitigated by applying smart access mechanisms and smart antennas. In this paper we analyze the performance of WANETs applying two-phase slotted carrier sense multiple access (CSMA) mechanism and utilizing directional antennas. We present simple expressions that enable a high accuracy evaluation of the network area spectral efficiency (ASE). The results show that directional antennas only affect the ASE through a scaling factor, which depends on the antennas pattern and the channel path loss. The ASE expression also provides a simple and accurate evaluation of the optimal system parameters, including the optimal network density, interference threshold and users' rates. In particular, the ASE gain for a CSMA WANET over an ALOHA WANET is shown to be approximated very well by the exponent of the back-off probability. The accuracy of the results and the usefulness of the optimization procedure are also illustrated through numerical simulations.

In this paper we analyze an adaptive downstream multichannel VDSL precoder that is based on error signal feedback. The analysis presents sufficient conditions for precoder convergence and an upper bound on the precoder steady state error. The paper also considers and analyzes the case of partial FEXT cancellation. The analysis shows that in some scenarios (and in particular in mixed-length binders) the use of partial FEXT cancellation is crucial to achieve precoder convergence in a reasonable time. Based on this analysis we determine that convergence is achievable in most practical channels. These bounds also allow for the proper setting of the convergence parameters. The paper presents several simulations to demonstrate the theoretical results. In these simulations, setting the precoder parameters according to the analysis leads to convergence in less than 400 OFDM symbols.

Probability control is a recently introduced concept that allows better mitigation of multiple access interference in CDMA networks. A probability controlled system uses non-continuous transmission, and reduces the interference by controlling the userspsila transmission probabilities. The advantages of probability control were proved by analysis of its signal to noise plus interference ratio (SINR) and its achievable mutual information rate. In this paper we take this research one step forward, and study the practical requirements from a system that implements probability control. We present a system structure that is based on convolutional codes, periodic puncturing and pseudo random interleaving, and define the required receiver structure. Performance analysis of the presented system shows significant gains over conventional systems.

Direct sequence code division multiple access (CDMA) systems that use non-continuous transmission were considered throughout the history of spread spectrum systems, but gained renewed interest with the emergence of impulse radio (IR) technology. Recently, several works had shown that in non- continuous CDMA, the transmission duty cycle (or transmission probability) has a significant effect on system performance. In this work we address the optimization of the performance of CDMA systems with adjustable transmission probabilities. We consider CDMA systems that implement non-continuous transmission by random puncturing, and study the system optimization with respect to both transmission powers (termed power control) and transmission probabilities (termed probability control). We show that the joint optimization has a significant performance advantage over the optimization with respect to transmissions powers only. For some cases we even show that the optimization with respect to transmission probabilities alone is sufficient to achieve optimal performance. In this part, we demonstrate the importance of probability control, by studying the case of frequency-flat slow-fading multiple access channel (MAC) and no spreading. We prove, for this special case, that mutual information rate optimization is achieved by probability control only, while power control is redundant. The theory is supported by simulation results, which show that the achievable rates of all users are better in a system that uses probability control instead of power control.

Code division multiple access (CDMA) systems commonly use power control mechanism to reduce the amount of interference between the users. In part I of this paper, we introduced the concept of probability control that optimizes system performance with respect to the users' transmission probabilities. The importance of probability control was demonstrated by proving that probability control alone optimizes the mutual information rates over a frequency-flat slow-fading multiple access channel. In this part we extend this result to the optimization of the average signal-to-noise plus interference ratio (SIR) in a CDMA system over a frequency-selective slow- fading channel model and any network topology. We prove that there is a group of CDMA receivers, in which the average SIR (ASIR) of all users is maximized using probability control (while all users transmit their maximal allowed power). This receivers group includes, among others, the common matched filter (MF) RAKE receiver, as well as the sophisticated minimal mean square error (MMSE) RAKE receiver. Simulations demonstrate for a 2- users scenario that both users achieve significantly higher ASIR using probability-control instead of power-control. Results are applicable both for CDMA and impulse radio (IR) systems.

Although communication systems are often analyzed under the assumption of prior knowledge of the channel, this is rarely the case in practical systems, which usually need to estimate the channel from the received communication signal. The analysis of channel capacity in the absence of prior channel knowledge had gained increasing interest in recent years, but this capacity is not yet known for the general case. In this paper we derive tight bounds on the capacity of the channel in the case of slow frequency selective fading channels with peak power constraint. We also show that in this case, a system that employs truncated Gaussian signaling and minimum Euclidean distance receiver can achieve information rates which are very close to the channel capacity.

This paper studies the fundamental transmission limits for ultra wideband (UWB) downlink broadcast channels. The significant contribution of this article is demonstrating the effectiveness of adaptive frequency allocation in UWB systems. We derive an expression for the ergodic sum-rate capacity of an UWB channel with perfect channel knowledge, and show the advantage of an adaptive system that uses channel state information (CSI), over a conventional, non-adaptive system. A capacity achieving system is also proposed. In this system, the transmitter assigns each frequency band to the user that has the best channel gain, and adaptively changes the bandwidth allocation according to the known channel state. The sum-rate capacity can be achieved in a fast fading channel. For a slow fading channel the system must apply fair scheduling to ensure service to all users, and the optimization must be performed for each channel realization. In this case, we also take advantage of the wide bandwidth of the UWB system and show the advantage of an frequency adaptive systems over non frequency adaptive systems

Impulse radio (IR) systems have drawn attention during the last few years. These systems are planned to coexist with narrowband systems without interfering them. Nevertheless, the narrowband systems can cause interference which may jam the IR receiver. This letter analyzes a low-complexity narrowband interference (NBI)-mitigation algorithm for IR systems, based on minimal mean-square error combining. Theoretical analysis reveals that these algorithms nearly eliminate the NBI. The concept is also extended to the case where the receiver has more correlators than channel taps.

Semi blind impulse radio (IR) is a low complexity receiver, which improves performance by employing prior knowledge of the pulse transmission times of all other users. In this paper we investigate the optimization of the operation of a semi-blind IR system as a multiuser, multiple-access system. We show that optimal semi-blind IR has significant performance improvement over a code division multiple access (CDMA) system. This performance increase is measured by the achievable rate region, and it is shown that using semi-blind IR, the rate of at least one of the users can be made higher, without decreasing the rate of any user.

A new Cramer-Rao lower bound for symbol timing recovery of linearly modulated (quadrature amplitude modulation) signals is presented. Contrary to some other works on the subject, the transmitted data is assumed to be unknown at the receiver. The bound is derived from a likelihood function that includes the symbol randomness. For large number of symbols, the bound is achievable at any signal-to-noise ratio. The separation of symbol timing recovery and phase recovery schemes is investigated using the new results. It is shown that the separation of these operations causes a degradation of less than 0.3 dB compared to joint phase and timing recovery. The bound is derived for symbol shaping limited to a single symbol length (i.e., no intersymbol interference.) Simulations for longer pulse shapes demonstrate that the new results provide better performance prediction than other known techniques.