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The application of hybrid precoding in millimeter wave (mm-wave) multiple-input multiple-output (MIMO) systems has been proven effective for reducing the number of radio frequency (RF) chains. However, the maximum number of independent data streams is conventionally restricted by the number of RF chains, which limits the spatial multiplexing gain. To further improve the achievable spectral efficiency (SE), in this paper we propose a generalized spatial modulation aided mm-wave MIMO system to convey an extra data stream via the index of the active antennas group, while no extra RF chain is required. Moreover, we propose a hybrid analog and digital precoding scheme for SE maximization. Based on a narrowband mm-wave-MIMO channel assumption, a closed-form lower bound is derived to quantify the achievable SE of the proposed system. By utilizing this lower bound as the cost function, a two-step algorithm is proposed to optimize the hybrid precoder. The proposed algorithm not only utilizes the concavity of the cost function over the digital power allocation vector but also invokes the convex $\ell _\infty$ relaxation to handle the non-convex constraint imposed by analog precoding. Finally, the proposed scheme is shown via simulations to outperform state-of-the-art mm-wave MIMO schemes in terms of achievable SE. [ABSTRACT FROM PUBLISHER]

Cooperative multicast has been demonstrated to achieve significant performance gain over the classic source–destination transmission paradigm by exploiting spatial diversity through the participation of multiple relay nodes. As a major technical challenge, the selection of relays for a multicast session has significant impact on the multicast performance. The challenge is even more pronounced when the number of channels is limited as the relay selection is in this context coupled with channel allocation. The goal of this paper is to design a fair multicast relay selection scheme with limited channel resources. Specifically, we establish an analytical framework for this joint relay selection and channel allocation problem and develop a lexicographic max–min multicast relay selection scheme. Our design consists of two technical steps. First, we consider the maximization of the minimal data rate. By decoupling relay selection and channel allocation, the problem is transformed to a max–min–max problem, which is difficult to solve. To make this problem tractable, we reformulate it as a convex optimization problem via relaxation and smoothing, and prove the asymptotic equivalence from a geometrical perspective. Second, we propose an adjustment algorithm based on the initial max–min solution, and prove that the proposed scheme achieves lexicographic optimality. Finally, our proposed algorithm is evaluated by simulation to show its superiority over the conventional schemes. [ABSTRACT FROM PUBLISHER]

In this paper, we present a distributed resource allocation mechanism in cognitive radio networks, based on a new coopetition methodology, which combines advantages of nodes' competition and cooperation. We postulate that this new method allows for fully distributed resource management between cognitive radio devices. The presented framework is generic, however, we consider it for the application in OFDMA networks. Coopetition takes the best from cooperative and competitive problem formulation, and provides the opportunity to control the balance between fairness and spectral efficiency (SE) of resource allocation. Simulation results confirm that coopetition allows for efficient resource utilization, and may be used practically in wireless cognitive networks. [ABSTRACT FROM AUTHOR]

Energy harvesting (EH) from ambient radio-frequency (RF) electromagnetic waves is an efficient solution for fully autonomous and sustainable communication networks. Most of the related works presented in the literature are based on specific (and small-scale) network structures, which although give useful insights on the potential benefits of the RF-EH technology, cannot characterize the performance of general networks. In this paper, we adopt a large-scale approach of the RF-EH technology and we characterize the performance of a network with random number of transmitter-receiver pairs by using stochastic-geometry tools. Specifically, we analyze the outage probability performance and the average harvested energy, when receivers employ power splitting (PS) technique for "simultaneous" information and energy transfer. A non-cooperative scheme, where information/energy are conveyed only via direct links, is firstly considered and the outage performance of the system as well as the average harvested energy are derived in closed form in function of the power splitting. For this protocol, an interesting optimization problem which minimizes the transmitted power under outage probability and harvesting constraints, is formulated and solved in closed form. In addition, we study a cooperative protocol where sources' transmissions are supported by a random number of potential relays that are randomly distributed into the network. In this case, information/energy can be received at each destination via two independent and orthogonal paths (in case of relaying). We characterize both performance metrics, when a selection combining scheme is applied at the receivers and a single relay is randomly selected for cooperative diversity. [ABSTRACT FROM PUBLISHER]

In cognitive radio networks, in order to avoid interference form secondary users to the primary license holders of the spectrum, reliable spectrum sensing is necessary. In scenarios where the noise samples are correlated, the spectrum sensing methods optimized considering impairment by independent noise samples will not provide optimum performances. To address this issue, a locally optimum detection method for random signals under a weakly correlated noise model over fading channels is proposed. The probabilities of false alarm and detection of the proposed detector in the low signal to noise ratio regime are analyzed. The average probabilities are calculated over different channel gains. Numerical and simulation results demonstrate the superiority of the proposed method over the known energy detection method with comparable complexities. Furthermore, we consider the scenario where the estimated correlation is different from the real correlation and investigate the effect of this correlation mismatch on the probabilities of false alarm and detection of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper considers a conditional decode-and-forward (DF) based cooperative system where a source (S) with multiple (M) antennas transmits information to a single-antenna destination (D) with the help of multiple (L ≤ M-1) single-antenna relays (R_i). The optimal transmit weighting vector at the source is not available in the literature due to the non-linear conditional DF operation, which renders the problem non-convex. To solve this problem, we first show that the optimal transmit vector for the single-relay system can be determined by comparing the S-D beamformer (maximum-ratio-transmit beamforming vector for the S-D link) with the one that utilizes "just sufficient" energy to activate the relay-link. However, it is difficult to directly apply the above idea to the multi-relay system, due to the fact that the S-R and S-D links are normally not orthogonal. To tackle this issue, we propose to utilize basis functions that are orthogonal to the S-D and S-R links, respectively, which enables the activating of one S-R link without considering the S-D link and the other S-R links. We then apply the new basis functions to the multi-relay system and propose a selective relay-activation algorithm, where the optimal solution is obtained by comparing the S-D beamformer with schemes that selectively activate different combinations of the relay-links. The selective relay-activation algorithm is different from the conventional water-filling in the sense that the energy is filled to discrete levels to activate the S-R links, a unique feature arising from the conditional DF operation. [ABSTRACT FROM PUBLISHER]

In this paper we propose a novel power adaptive network coding (PANC) for a non-orthogonal multiple-access relay channel (MARC), where two sources transmit their information simultaneously to the destination with the help of a relay. In contrast to the conventional XOR-based network coding (CXNC), the relay in PANC generates network coded symbols by considering the coefficients of the source-to-relay channels, and forwards each symbol with a pre-optimized power level. Specifically, by defining a symbol pair as two symbols from the two sources, we first derive the expression of symbol pair error rate (SPER) for the system. Noting that deriving the exact SPER are complex due to the irregularity of the decision regions caused by random channel coefficients, we propose a coordinate transform (CT) method on the received constellation to simplify the derivations of the SPER. Next, we obtain the optimal power level by decomposing it as a multiplication of a power scaling factor and a power adaptation factor. We prove that with the power scaling factor at the relay, our PANC scheme can achieve a full diversity gain, i.e., an order of two diversity gain, while the CXNC can achieve only an order of one diversity gain. In addition, we optimize the power adaptation factor at the relay to minimize the SPER at the destination by considering of the relationship between SPER and minimum Euclidean distance of the received constellation, resulting in an improved coding gain. Simulation results show that (1) the SPER derived based on our CT method can well approximate the exact SPER with a much lower complexity; (2) the PANC scheme with power adaptation optimizations and power scaling factor design can achieve a full diversity, and obtain a much higher coding gain than other network coding schemes. [ABSTRACT FROM PUBLISHER]

Cloud Computing is becoming a mainstream paradigm, as organizations, large and small, begin to harness its benefits. This novel technology brings new challenges, mostly in the protocols that govern its underlying infrastructure. Traffic engineering in cloud data centers is one of these challenges that has attracted attention from the research community, particularly since the legacy protocols employed in data centers offer limited and unscalable traffic management. Many advocated for the use of VLANs as a way to provide scalable traffic management, however, finding the optimal traffic split between VLANs is the well known NP-Complete VLAN assignment problem. The size of the search space of the VLAN assignment problem is huge, even for small size networks. This paper introduce a novel decomposition approach to solve the VLAN mapping problem in cloud data centers through column generation. Column generation is an effective technique that is proven to reach optimality by exploring only a small subset of the search space. We introduce both an exact and a semi-heuristic decomposition with the objective to achieve load balancing by minimizing the maximum link load in the network. Our numerical results have shown that our approach explores less than 1% of the available search space, with an optimality gap of at most 4%. We have also compared and assessed the performance of our decomposition model and state of the art protocols in traffic engineering. This comparative analysis proves that our model attains encouraging gain over its peers. [ABSTRACT FROM PUBLISHER]

Dynamic spectrum management is recognized as a key technique to tackle interference in multi-user multi-carrier communication systems and networks. However existing dynamic spectrum management algorithms may not be suitable when the available computation time and compute power are limited, i.e., when a very fast responsiveness is required. In this paper, we present a new paradigm, theory and algorithm for real-time dynamic spectrum management (RT-DSM). Specifically, a RT-DSM algorithm is real-time in the sense that it can be stopped at any point in time while guaranteeing a feasible and improved solution. This is enabled by the introduction of a novel difference-of-variables (DoV) transformation and problem reformulation, for which a primal coordinate ascent approach is proposed with exact line search via a logarithmically-scaled grid search. The proposed algorithm is referred to as iterative power difference balancing (IPDB). Simulations for different realistic wireline and wireless interference-limited systems demonstrate its good performance, low complexity and wide applicability under different configurations. [ABSTRACT FROM PUBLISHER]

Certain optimization problems in communication systems, such as limited-feedback constant-envelope beamforming or noncoherent M-ary phase-shift keying (MPSK) sequence detection, result in the maximization of a fixed-rank positive semidefinite quadratic form over the MPSK alphabet. This form is a special case of the Rayleigh quotient of a matrix and, in general, its maximization by an MPSK sequence is \mathcalNP-hard. However, if the rank of the matrix is not a function of its size, then the optimal solution can be computed with polynomial complexity in the matrix size. In this work, we develop a new technique to efficiently solve this problem by utilizing auxiliary continuous-valued angles and partitioning the resulting continuous space of solutions into a polynomial-size set of regions, each of which corresponds to a distinct MPSK sequence. The sequence that maximizes the Rayleigh quotient is shown to belong to this polynomial-size set of sequences, thus efficiently reducing the size of the feasible set from exponential to polynomial. Based on this analysis, we also develop an algorithm that constructs this set in polynomial time and show that it is fully parallelizable, memory efficient, and rank scalable. The proposed algorithm compares favorably with other solvers for this problem that have appeared recently in the literature. [ABSTRACT FROM PUBLISHER]

This paper presents a practical performance analysis of an orthogonal space-time block code (OSTBC) based multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system in the presence of nonlinear power amplifiers (PAs). The equivalent single-input single-output (SISO) scalar model is introduced and this then is used to construct a model for the nonlinear MIMO-OFDM system. Based on an unique inter-modulation product (IMP) analysis, it is shown how the receiver signal-to-noise ratio (SNR) may be derived to a polynomial based function of the system operating point. It is also shown that expressions for the asymptotical behavior of this SNR, when the linear and highly nonlinear PA operations are applied, may also be derived. Based on these derivations, it is further shown that the optimal system operating point, which corresponds to the maximum receiver SNR and SEP lower bound, can be identified and be derived to a polynomial based expression. Additionally, a general expression for the different integral expressions of SEP for the phase shift keying (PSK) and quadrature amplitude modulation (QAM) signals is found. By means of these analytical results, it was found possible to advance analytical explanations of observed behaviour in simulations and also to provide a practical analysis of performance optimization of nonlinear MIMO-OFDM systems. [ABSTRACT FROM PUBLISHER]

Radio Frequency IDentification (RFID) is intended to supplant legacy (optical) bar code scanning technology found in many logistic and retail applications. RFID is distinguished by inexpensive, low power and compact form factor tags, whose longevity and efficacy are predicated on using passive communication techniques and on-tag power harvesting. Such tags employ backscatter modulation, which does not require any active RF components. As a result, backscatter has become an attractive design choice for short-range communications in power constrained wireless sensor networking scenarios. The purpose of this work is two-fold. First, it aims to expose backscatter communication as an emerging topic to a communication systems-theoretic audience. Since backscatter modulation and on-tag power harvesting efficiency are coupled, it is necessary to re-examine notions of power and spectral efficiency from an energy-constraint perspective; this leads to novel coded modulation schemes for future RFID systems. Further, we investigate RFID MIMO systems where the channel fading encountered has different statistics than the classical Rayleigh fading model. In turn,the trade off between diversity order and spatial multiplexing gains are distinct from wide-area MIMO. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the issue of throughput and packet drop rate (PDR) optimization as two performance metrics for delay sensitive applications in network coded time division duplex (TDD) satellite systems with large round trip times (RTTs). We adopt random linear network coding (RLNC) and our purpose is to obtain the optimum RLNC-based transmission strategy. We start with a single-user case and propose a systematic framework to investigate the advantage of using feedback by comparing feedback-free and feedback schemes. Showing analytically that the feedback-free scheme gives better performance for our system of interest, we extend it to multi-user broadcast case. To this end, we consider a number of different broadcast scenarios and optimize the system parameters such that the best overall performance is achieved. Furthermore, the complicated interplay of the mean throughputs and PDRs of different users with different packet erasure conditions is discussed. Finally, it is shown that the optimized feedback-free RLNC broadcast scheme works close enough to an idealistic RLNC scheme, where the complete and immediate knowledge about the reception status of all users is assumed to be available at the sender. [ABSTRACT FROM PUBLISHER]

The interference to the primary receiver (PR) is a critical issue in the resource allocation of cognitive radio (CR) networks. For instance, the nonlinearity of the power amplifier (PA) causes nonlinear interference to the PRs. This paper studies the power allocation in cognitive radio networks by considering the nonlinear effects of the PA on the received signal-to-noise ratio (SNR) at the secondary receiver (SR) and the adjacent channel interference (ACI) to the PRs. A nonlinear PA with limited dynamic range and a lower limit on the transmit power is assumed for the secondary transmitter (ST). To control the resulting ACI from the ST to the PRs, the PA needs to be turned off in some fading blocks. To investigate the throughput, an analytical expression for the probability of data transmission between the secondary users is derived as a function of the interference temperature limits of the PRs. All analyses are performed for both peak and average ACI power constraints. Through theoretical analysis and simulation studies, maximum achievable average SNR at the SR is investigated. Moreover, the throughput degradation is studied and it is observed that the average ACI power constraints result in the better performance than the peak ones. [ABSTRACT FROM PUBLISHER]

Due to limited cooperation between the primary users and the secondary users (SUs) in practical spectrum sharing systems, the secondary transmitters and receivers are assumed to have partial channel state information related to the primary receiver. Under such an assumption, this work investigates power allocation strategies for the SUs subject to an outage probability constraint on the primary transmission and a peak transmit power constraint on the secondary transmission. The challenge lies in the non-convexity of the outage probability constraint. Firstly, we prove that strong duality holds and that the Karush-Kuhn-Tucker (KKT) conditions are necessary for optimality. The optimal solution is then derived by addressing the optimality issues of the KKT solutions. Secondly, in order to further reduce the algorithmic complexity, two suboptimal strategies are proposed. The first one is designed based on several simplifications of the optimal strategy. The second one is derived from the convex relaxation of the non-convex primal problem, which corresponds to the problem with the conventional interference temperature constraint. The performance for both suboptimal strategies is derived in closed form. All proposed strategies are shown to outperform non-adaptive power transmission. The near-optimality of the two suboptimal strategies is also validated, in particular for the first one. [ABSTRACT FROM PUBLISHER]

The article discusses a non-convex optimization framework for the two-user MISO interference channel, which is based on monotonic optimization by outer polyblock approximation. The authors first presented objective functions that represents terms of differences of monotonic increasing functions and after it, problems were reformulated as maximization of increasing functions over normal constraint sets. The tests revealed the advantages of the proposed framework over existing ones.

Channel-optimized quantizer index assignment and maximum a posteriori (MAP) decoding have been extensively studied for error-resilient communications. An interesting and largely untreated problem is how to optimize the index assignment with respect to joint source-channel MAP decoding. In this paper we formulate the above problem as one of quadratic assignment, and discuss its solutions from very general to some special cases. For highly correlated Gaussian Markov sources and Hamming distortion, we can construct the optimal index assignment analytically. For general cases, simulated annealing algorithm is adopted to search for the optimal index assignment. Experimental results are presented to demonstrate the performance improvement of the index assignments optimized for MAP decoding over those designed for hard-decision decoding (e.g. Gray code). The reduction of symbol error rate and mean squared error can be as large as 40% and 50% respectively for highly correlated Gaussian Markov sources. [ABSTRACT FROM AUTHOR]

This paper analyzes the error performance of a coded cooperative diversity system employing the Euclidean superposition of two BPSK-modulated signals. For an example using a convolutional code on block fading channels, the results show excellent agreement with computer simulations. The analysis makes it possible to optimize the power allocation between the local and relay signals numerically, circumventing the need for time consuming Monte Carlo simulations. Similarly, the analysis demonstrates how the power allocation can be "tuned" to compensate for unbalanced uplink channels and/or to provide unequal error protection to the data from the two cooperating nodes. [ABSTRACT FROM AUTHOR]

The windows for achieving good multiple-access performance of multicarrier code-division multiple-access (MC- CDMA) systems employing minimum mean-squared error receivers are studied. The mean-squared error (MSE) is used as the performance metric for the optimization. In a simplified two-user system, the rectangular window is found to be optimum while regarded as an inferior window in orthogonal frequency-division multiplexing systems because of its spectral inefficiency. Necessary conditions are given for improving the performances of spectrally efficient windows by exploiting the cyclic prefix and oversampling in the frequency domain. [ABSTRACT FROM AUTHOR]

Rate-constrained power minimization (PMIN) over a code division multiple-access (CDMA) channel with correlated noise is studied. PMIN is shown to be an instance of a separable convex optimization problem subject to linear ascending constraints. PMIN is further reduced to a dual problem of sum-rate maximization (RMAX). The results highlight the underlying unity between PMIN, RMAX, and a problem closely related to PMIN but with linear receiver constraints. Subsequently, conceptually simple sequence design algorithms are proposed to explicitly identify an assignment of sequences and powers that solve PMIN. The algorithms yield an upper bound of 2N - 1 on the number of distinct sequences where N is the processing gain. The sequences generated using the proposed algorithms are in general real-valued. If a rate-splitting and multi-dimensional CDMA approach is allowed, the upper bound reduces to N distinct sequences, in which case the sequences can form an orthogonal set and be binary ±1-valued. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the transmission power allocation for the support of broadcast/multicast services (BMSs) in multi-cell OFDM systems. We consider a cooperative architecture for distribution of the BMS data where the copies of the same data are transmitted by multiple base stations (BSs) in a synchronized manner and then aggregated at the receiving users. Under this architecture, we develop a power allocation scheme that optimizes the transmission power of the multiple BSs on each sub-channel to maximize the total data rate. The optimal power allocation turns out to take the form of iterative water-filling, particularly when heterogeneous modulation and coding schemes are allowed in each sub-channel. In addition, we study the two special cases where the BMS system has extended or limited capabilities: First, we consider the BMS system that supports a more sophisticated video coding technique, fine granularity scalability (FGS) video coding, which encodes the BMS data into base layer and enhancement layer. Taking the layered structure into account, we propose a power allocation scheme that maximizes the data rate of the enhancement layer while guaranteeing the minimum data rate requirement of the base layer. Second, we consider the BMS system that only allows average channel state information of users to be available at the resource manager. In this case, as it is not possible to guarantee successful transmission of every data due to instant deep fading, we propose a power allocation scheme that minimizes the probability of transmission failure. Simulation results reveal that the cooperative distribution system performs far better than the non-cooperative distribution system and the proposed power allocation schemes outperform the equal power allocation scheme significantly. [ABSTRACT FROM AUTHOR]

We consider schemes for decentralized cross-layer optimization of multichannel random access by exploiting local channel state and traffic information. In the network we are considering, users are not necessarily within the transmission ranges of all others; therefore, when a user is transmitting, it may only interfere with some users, which is different from most existing channel aware Aloha schemes. Besides, we also consider complicated traffic distribution, e.g. each user may choose to send packets to or receive packets from different users simultaneously. We develop decentralized optimization for multichannel random access (DOMRA). DOMRA consists of three steps: neighborhood information collection, transmission control of the MAC layer based on the instantaneous channel state information, and power allocation for each traffic flow on each subchannel. Simulation results demonstrated that DOMRA significantly outperforms existing channel aware Aloha schemes due to its exploitation of both multiuser diversity through cross-layer design and the inhomogeneous characteristics of traffic spatial distribution in the network. Besides, DOMRA performs closely to the globally optimum solution, which requires full network knowledge to be obtained. DOMRA can be applied to different types of wireless networks, such as wireless sensor networks and mobile ad hoc networks, to improve quality of service. [ABSTRACT FROM AUTHOR]

A performance optimization based on the optimal switching threshold(s) for a multi-branch switched diversity system is discussed in this paper. For the conventional multi-branch switched diversity system with a single switching threshold, the optimal switching threshold is a function of both the average channel SNR and the number of diversity branches, where computing the optimal switching threshold is not a simple task when the number of diversity branches is high. The newly proposed multi-branch switched diversity system is based on a sequence of switching thresholds, instead of a single switching threshold, where a different diversity branch uses a different switching threshold for signal comparison. Thanks to the fact that each switching threshold in the sequence can be optimized only based on the number of the remaining diversity branches, the proposed system makes it easy to find these switching thresholds. Furthermore, some selected numerical and simulation results show that the proposed switched diversity system with the sequence of optimal switching thresholds outperforms the conventional system with the single optimal switching threshold. [ABSTRACT FROM AUTHOR]

Selection amplify-and-forward (SAF) relaying, which has been shown to be optimal under the constraints of localized channel information at the relays and a constant relay power allocation (PA) template, is shown to be globally strictly suboptimal. A necessary condition for the outage optimality of the SAF PA, and an exponentially vanishing upper bound on the probability of the SAF optimality are derived. [ABSTRACT FROM AUTHOR]

We consider the problem of differentiated rate scheduling for the downlink (i.e., multi-antenna broadcast channel), in the sense that the rates required by different users must satisfy certain constraints on their ratios. When full channel state information (CSI) is available at the transmitter and receivers, the problem can be readily solved using dirty paper coding (DPC) and the application of convex optimization techniques on the dual problem which is the multiple access channel (MAC). Since in many practical application full CSI may not be feasible and computational complexity prohibitive when the number of users is large, we focus on other simple schemes that require very little CSI: time-division opportunistic (TO) beamforming where in different time slots (of different lengths) the transmitter performs opportunistic beamforming to .the users requiring the same rate, and weighted opportunistic (WO) beamforming where the random beams are assigned to those users having the largest weighted SINR. For single antenna systems we also look at the capacity-achieving superposition coding (SC) scheme. In all cases, we determine explicit schedules to guarantee the rate constraints and show that, in the limit of large number of users, the throughput loss compared to the unconstrained throughput (sum-rate capacity) tends to zero. We further provide bounds on the rate of convergence of the sum-rates of these schemes to the sum-rate capacity. Finally, we provide simulation results of the performance of different scheduling schemes considered in the paper. [ABSTRACT FROM AUTHOR]

This correspondence corrects an error in our paper titled, "On the Optimality of Beamforming with Quantized Feedback", published in the IEEE Transactions on Communications, vol. 55, no. 12, pp. 2288-2302, Dec. 2007. [ABSTRACT FROM PUBLISHER]