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The wireless industry is moving towards developing smart cellular architectures that dynamically adjust the use of the network elements according to the service demand, and automating their operations in order to minimize both capital expenditure (CAPEX) and operation expenditure (OPEX). This involves developing efficient and unsupervised radio access network (RAN) planning, which has a direct impact on the system performance and CAPEX. This intelligent cellular planning aims at providing the base stations (BSs) configurations (e.g., coverage, user associations and antenna radiation pattern) that minimize the number of deployed BSs and meet the requirements in terms of coverage and capacity. The cellular planning optimization problem has been shown to be complex and non-scalable. Moreover, most of the existing cellular planning techniques result in an over or under provisioning architecture. Motivated by the above, we propose in this paper a novel and efficient unsupervised planning process. We make use of statistical machine learning (SML) to solve the problem at hand. The core idea of SML is that the planning parameters are treated as random variables. The parameters that maximize the corresponding joint probability distribution, conditioned on observations of users’ positions, are learned or inferred using Gibbs sampling theory and Bayes’ theory. To apply this theory to the planning problem, we make significant efforts to properly formulate the problem to be able to incorporate the constraints into the inference process and extract the planning parameters from the inferred model. Through several numerical examples, we compare the performance of the proposed approach to clustering-based and optimization-based existing planning approaches, and demonstrate the efficacy of our approach. We also demonstrate how our approach can leverage existing cellular infrastructures into the new design.

Next-generation cellular systems are anticipated to support 100 times higher data rates (ultra-high rate) compared with the fourth generation (4G) of cellular systems. It is, therefore, necessary to develop novel spectrally efficient uplink/downlink techniques. Multiple techniques have been proposed, including the so-called non-orthogonal multiple access (NOMA) technique. However, the spectral efficiency gains achieved by NOMA over OMA techniques have been shown to be modest. Recently, we proposed a spectrally efficient technique for the downlink channel, which involves exploiting similarities among users’ short bit blocks, where we showed that spectral efficiency gains of up to three times that of OMA schemes can be achieved. However, the technique cannot be extended to the uplink scenario because users are not aware of each other’s bit block. To this end, we propose in this paper a spectrally efficient scheme for the uplink channel, where we exploit the similarity between the short bit blocks of the uplink and downlink sequences corresponding to one user. The downlink bit sequences are those received by a user from the base station (BS). It is assumed that the BS keeps track of the bit sequences transmitted on the downlink channel to different users. The uplink and downlink bit sequences, which are assumed to be uncorrelated, are divided into bit blocks of short lengths, and then, the similarity between those blocks is extracted. Once each user determines its similarity index (i.e., the number of similar bit blocks) between its own bit sequence and its respective downlink bit sequence, this information is communicated with the BS, which will, in turn, select the user with the largest similarity index to transmit during that resource block. The same process repeats every resource block where the user with the maximum similarity index is always selected. We propose a simple overhead exchange algorithm that facilitates the exchange of the information on the similarity indexes between the users and the BS, where we assume that this exchange of information is done through a control channel. The performance of the proposed scheme and the overhead exchange algorithm is investigated analytically and by Monte Carlo simulations. Among the parameters that we incorporate into the analysis are the user density, the length of bit blocks used to check the similarity index, and the channel correlation. We show that spectral efficiency gains of approximately two times that of OMA schemes can be achieved.

This paper investigates the secrecy performance of the multiple-input single-output visible light communication (VLC) wiretap channel. The considered system model comprises three nodes: a transmitter (Alice) equipped with multiple fixtures of LEDs, a legitimate receiver (Bob), and an eavesdropper (Eve), each equipped with one photo-diode. The VLC channel is modeled as a real-valued amplitude-constrained Gaussian channel. Eve is assumed to be randomly located in the same area as Bob. Due to this, artificial noise-based beamforming is adopted as a transmission strategy in order to degrade Eve’s signal-to-noise ratio. Assuming discrete input signaling, we derive an achievable secrecy rate in a closed-form expression as a function of the beamforming vectors and the input distribution. We investigate the average secrecy performance of the system using stochastic geometry to account for the location randomness of Eve. We also adopt the truncated discrete generalized normal (TDGN) as a discrete input distribution. We present several examples through which we confirm the accuracy of the analytical results via Monte Carlo simulations. The results also demonstrate that the TDGN distribution, albeit being not optimal, yields performance close to the secrecy capacity.

Based on the concept of reconfigurable antennas (RAs), space-shift keying (SSK)-RA has been recently proposed as a novel transmission scheme to improve the performance of SSK. In this context, it has been shown that RAs’ reconfigurable properties can be used as additional degrees of freedom to enhance the throughput, implementation complexity, and error performance of SSK. In this paper, we study the implementation of SSK-RA within underlay cognitive radio systems in an effort to improve the performance of the secondary user while verifying the constraints set by the primary user (PU). Taking advantage of the interplay between RAs and the propagation channels for both the secondary and interference links, we propose an RA-based scheme with beam-direction reconfiguration aiming at improving the secondary system’s performance while verifying an outage interference constraint to the PU. In this paper, we analyze the performance of the proposed scheme in Rician fading channels and provide simulation examples confirming these analytical results. The proposed schemes are shown to offer enhanced bit error rate performance and lower implementation complexity when compared with conventional antenna-based spectrum sharing systems.

We have recently introduced adaptive spatial modulation (ASM) for multiple antenna systems, with the aim of improving the energy efficiency through spatial modulation (SM) and improving the average spectral efficiency (ASE) through adaptive modulation (AM). In this paper, we extend ASM to cognitive radio (CR) systems in an effort to improve the secondary system's performance in terms of energy efficiency and ASE. To this end, we propose two ASM schemes, one referred to as fixed power scheme (FPS) and the other as adaptive power scheme (APS). In both schemes, the secondary transmitter (ST) has limited knowledge of the channel state information (CSI) of the interference link. The difference between the two schemes, however, lies in the way the limited CSI is used to adapt the transmit power and/or modulation. As a benchmark, we also consider the scenario where the ST has perfect knowledge of the CSI of the interference link. For all cases, we analyze the performance in terms of ASE, average delay, and bit error rate (BER). We show that the proposed schemes offer tradeoffs in terms of the previously mentioned performance metrics, thus offering different options for applying ASM to CR systems. We also provide several simulation examples through which we corroborate the analytical results.

We consider in this paper distributed beamforming for two-way cognitive radio networks in an effort to improve the spectrum efficiency and enhance the performance of the cognitive (secondary) system. In particular, we consider a spectrum sharing system where a set of amplify-and-forward (AF) relays are employed to help a pair of secondary transceivers in the presence of multiple licensed (primary) users. The set of relays participate in the beamforming process, where the optimal beamformer weights are obtained via a linear optimization method. For this system, we investigate the transmission protocols over two and three time-slots. To study and compare the performance tradeoffs between the two transmission protocols, for both of them, we derive closed-form expressions for the cumulative distribution function (CDF) and the moment generating function (MGF) of the equivalent end-to-end signal-to-noise ratio (SNR) at the secondary receiver. We analyze the performance of the proposed methods where closed-form expressions for the user outage probability and the average error probability are derived for independent and identically distributed Rayleigh fading channels. Numerical results demonstrate the efficacy of beamforming in enhancing the secondary system performance in addition to mitigating the interference to the primary users. In addition, our results show that the three time-slot protocol outperforms the two time-slot protocol in certain scenarios where it offers a good compromise between bandwidth efficiency and system performance.

Multiuser cooperative schemes usually rely on relay selection or channel selection to avoid deep fading and achieve diversity while maintaining acceptable spectral efficiency. In some applications such as underwater acoustic communications, the low speed of the acoustic wave results in a very long delay between the channel state information (CSI) measurement time and the relay assignment time, which leads to a severely outdated CSI. To remedy this, we propose distributed coding schemes that aim at achieving good diversity-multiplexing trade-off (DMT) for multiuser scenarios where CSI is not available for resource allocation. We consider a network with multiple source nodes, multiple relay nodes, and a single destination. We first introduce a distributed linear block coding scheme, including Reed-Solomon codes, where each relay implements a column of the generator matrix of the code, and soft decision decoding is employed to retrieve the information at the destination side. We derive the end-to-end error performance of this scheme and show that the achievable diversity equals the minimum Hamming distance of the underlying code, while its DMT outperforms that of existing schemes. We extend the proposed scheme to distributed convolutional codes, and show that achieving higher diversity orders is also possible.

In this paper, we use joint distributed beamforming and cooperative relaying in cognitive radio relay networks in an effort to enhance the spectrum efficiency and improve the performance of the cognitive (secondary) system. In particular, we consider a spectrum sharing system where a set of potential relays are employed to help a pair of secondary users in the presence of a licensed (primary) user. Among the available relays, only the reliable ones participate in the beamforming process, where the beamformer weights are obtained based on a linear optimization method. We investigate two well-known strategies, namely, selection decode-and-forward (SDF) and amplify-and-forward (AF) relaying in conjunction with distributed optimal beamforming. However, given the complexity of the performance analysis with optimal beamforming, we use zero forcing beamforming (ZFB), and compare both approaches through simulations. In this context, for SDF, we derive expressions for the probability density function (PDF) of the received signal-to-interference noise ratio (SINR) at the relays as well as at the secondary destination. As for the AF scheme, we obtain the exact expression for the cumulative distribution function (CDF) and the moment generating function (MGF) of the equivalent end-to-end SNR at the secondary destination. For both schemes, we derive closed-form expressions for the outage probability and bit error rate (BER) over independent and identically distributed Rayleigh fading channels for binary phase shift keying (BPSK) and M-ary quadrature amplitude modulation (M-QAM) schemes. Numerical results demonstrate the efficacy of the proposed scheme in improving the outage and BER performance of the secondary system while limiting the interference to the primary system. In addition, the results show the effectiveness of the combination of the cooperative diversity and distributed beamforming in compensating for the loss in the secondary system's performance due to the primary user's co-channel interference (CCI).

This paper presents an optimization framework for a wireless sensor network whereby, in a given route, the optimal relay selection and power allocation are performed subject to signal-to-noise ratio constraints. The proposed approach determines whether a direct transmission is preferred for a given configuration of nodes, or a cooperative transmission. In the latter case, for each node, data transmission to the destination node is performed in two consecutive phases: broadcasting and relaying. The proposed strategy provides the best set of relays, the optimal broadcasting power and the optimal power values for the cooperative transmission phase. Once the minimum-energy transmission policy is obtained, the optimal routes from every node to a sink node are built-up using cooperative transmission blocks. We also present a low-complexity implementation approach of the proposed framework and provide an explicit solution to the optimization problem at hand by invoking the theory of multi-parametric programming. This technique provides the optimal solution as a function of measurable parameters in an off-line manner, and hence the on-line computational tasks are reduced to finding the parameters and evaluating simple functions. The proposed efficient approach has many potential applications in real-world problems and, to the best of the authors' knowledge, it has not been applied to communication problems before. Simulations are presented to demonstrate the efficacy of the approach.

We address in this paper the challenge of coping with asymmetric data rates in two-way relay channels. We consider a relay network comprising two sources and one relay. The sources communicate at different rates through the relay. That is, we assume that one source uses M 1 -QAM (quadrature amplitude modulation) and the other uses M 1 /M 2 -QAM hierarchical modulation where M 1 ≠ M 2 . For the underlying network, we consider two decode-and-forward (DF) relaying schemes. One scheme combines hierarchical zero padding and network coding (HZPNC) at the relay. The novelty of this scheme lies in the way the two signals (that have different lengths) are network-coded at the relay. The other scheme is referred to as opportunistic user selection (OUS) where the user with a better end-to-end channel quality is given priority for transmission. We analyze both schemes where we derive closedform expressions for the end-to-end (E2E) bit error rate (BER). Since the two schemes offer a trade-off between performance and throughput, we analyze and compare both schemes in terms of channel access probability and average throughput. We show that HZPNC offers better throughput and fairness for both users, whereas OUS offers better performance. We also compare the performance of HZPNC with existing schemes including the original zero padding, nesting constellation modulation and superposition modulation. We show through examples the superiority of the proposed HZPNC scheme in terms of performance and/or reduced complexity. Scopus

Non-orthogonal multiple access (NOMA) has been proposed as an alternative to orthogonal multiple access (OMA) in an effort to enhance the spectral efficiency of 5G cellular systems. However, the NOMA throughput gain relative to that of OMA has been shown to be modest. In this paper, we propose a novel NOMA scheme that exploits the partial overlap (i.e., similarity) among users bit sequences at the base station (BS). Specifically, users bit sequences are divided into blocks of short lengths, i.e., short bit sequences. Then, one user is selected and served during a given transmission time interval (TTI). Users whose bit sequences partially overlap with the bit sequence of the served user are also (partially) served during the same TTI. At the receiving end, the receiver corresponding to the served user recovers its entire bit sequence, whereas the partially served users recover their corresponding overlapping bit blocks and ignore the rest of the sequence. The performance of the proposed scheme is analyzed in terms of the overall throughput. We show that a throughput gain of up to three times that of existing OMA schemes can be achieved. Moreover, we show that the average rate per user decreases slightly as the number of users increases, whereas it linearly decreases with the number of users in existing NOMA schemes. We stress here that the proposed scheme completely differs from existing NOMA schemes as the latter schemes are based on power allocation at the BS where successive interference cancellation is normally used. The implication of this is that the proposed scheme provides substantial throughput gains without causing interference among users and without adopting a specific power allocation at the BS.

In this paper, we consider antenna/relay selection for coded cooperative networks in an effort to improve their end-to-end performance by improving the detection reliability at the relay nodes. Considering amplify-and-forward (AF) relaying, we analyze a previously proposed distributed coded cooperation scheme in conjunction with antenna/relay selection. Specifically, we derive upper bounded expressions for the bit error rate assuming M-ary phase shift keying (M-PSK) transmission. Our analytical results show that the maximum diversity order of the system is maintained for the entire range of symbol error rate of interest, unlike the case without antenna/relay selection. Several numerical and simulation results are presented to demonstrate the efficacy of the proposed scheme.

This paper presents a new blind carrier frequency offset (CFO) estimation scheme for orthogonal frequency division multiplexing (OFDM) systems with constant modulus (CM) signaling. Both single-input single-output (SISO) systems and multiple-input multiple-output (MIMO) systems with orthogonal space-time block coding are considered. The proposed scheme is based on the reasonable assumption that the channel frequency response changes slowly in the frequency domain, which implies that the channel frequency response on two consecutive sub- carriers is approximately the same. Based on this assumption, cost functions are derived in closed-form, which minimize the difference between the signal power of two neighboring subcarriers. The identifiability of the proposed scheme is mathematically proved, which implies that minimizing the derived cost function gives an approximate estimate of the CFO. We demonstrate that the proposed scheme provides an excellent trade-off between complexity and performance as compared to prominent existing estimation schemes.

This paper addresses the problem of Doppler spread and carrier frequency offset (CFO) estimation under flat-fading Rayleigh channels. We develop a new low-cost and robust approximate maximum likelihood (ML) estimator for these two key parameters that builds upon an elegant two-ray approximation model of the channel’s covariance matrix. The latter is then inverted analytically thereby yielding a closed-form expression for the underlying log-likelihood function that is prone to easy evaluation by the fast Fourier transform. Computer simulations show that the new estimator is accurate over wide ranges of the Doppler spread and CFO parameters. Moreover, it outperforms many state-of-the-art techniques under the adverse conditions of short data records and/or low SNR thresholds. Most prominently, it exhibits an unprecedented robustness to the Doppler spectrum shape of the channel since it does not require its a priori knowledge.