Total Transmit Power Constraint Research Articles

Cross-layer Joint Relay Selection and Power Allocation Scheme for Cooperative Relaying System

A novel cross-layer joint relay selection and power allocation (CL-JRSPA) scheme over physical layer and data-link layer is proposed for cooperative relaying system in this paper. Our goal is finding the optimal relay selection and power allocation scheme to maximize system achievable rate when satisfying total transmit power constraint in physical layer and statistical delay quality-of-service (QoS) demand in data-link layer. Using the concept of effective capacity (EC), our goal can be formulated into an optimal joint relay selection and power allocation (JRSPA) problem to maximize the EC when satisfying total transmit power limitation. We first solving optimal power allocation (PA) problem with Lagrange multiplier approach, and then solving optimal relay selection (RS) problem. Simulation results demonstrate that CL-JRSPA scheme gets larger EC than other schemes when satisfying delay QoS demand. In addition, the proposed CL-JRSPA scheme achieves the maximal EC when relay located approximately halfway between source and destination, and EC becomes smaller when the QoS exponent becomes larger.

Resource Allocations for Secure Cognitive Satellite-Terrestrial Networks

Cognitive satellite-terrestrial networks (STNs) have been recognized as the promising architecture for addressing spectrum scarcity in the next generation communication networks. In this letter, we investigate the secure transmission schemes in the cognitive STNs where the interference from terrestrial base station (BS) is introduced to enhance security of the satellite link. Our objectives are to minimize the transmit power by jointly optimizing the cooperative beamforming and artificial noise (AN) while guaranteeing the secrecy rate constraint for satellite link, the information rate constraint for terrestrial link and the total transmit power constraint. Both scenarios of the perfect and imperfect channel cases are respectively considered. These constraints make the optimization problems formulated non-convex and challenging, which are efficiently solved via certain transformations to be formulated more tractable versions, respectively. Numerical results are provided to corroborate the proposed schemes.

Both the single user and multi user MIMO system design with individual transmit power constraint and improper constellation

This work address the problem of designing joint optimum transceiver for both single-user (SU) and multi-user (MU) MIMO system. Most of the previous works on both SU and MU-MIMO system, the joint precoder and decoder designs are based on the total transmit power constraint (TTPC) with proper modulation techniques. On the other hand, in practice, individual transmit power constraint (ITPC) is more realistic as the power at each antenna at the transmitter is restricted independently by the linearity of the power amplifier. In this work, a minimum total mean squared error (TMSE) design is formulated as a non-convex optimisation problem. This formulation is under equal power allocation (EPA) and the power constraint that jointly meets both EPA and TTPC (i.e., ITPC). The closed-form optimum linear precoder and decoder for SU-MIMO systems with an improper modulation are determined by solving this non-convex optimisation problem. It considers both the perfect and imperfect channel state information (CSI) is available at both the transmitter and receiver. The simulation results show the performance improvement of the proposed work over conventional work in terms of bit error rate (BER).

Goodput Maximization of HARQ-IR Over Arbitrarily Correlated Rician Fading Channels

This paper investigates the optimal design of hybrid automatic repeat request with incremental redundancy (HARQ-IR) over arbitrarily correlated Rician fading channels for goodput maximization. With practical consideration of both the channel time correlation and line-of-sight (LOS) links, theoretical analysis and optimal design of HARQ-IR become very challenging. To address them, asymptotic outage analysis is first carried out to not only gain meaningful insights but also facilitate the optimal design. With simple forms of asymptotic expressions derived, joint optimization of the transmission powers and rate aiming at goodput maximization under average total transmission power constraint is enabled and solved analytically. The optimal goodput is also derived in closed form, with which meaningful insights can then be extracted. Particularly, the scaling law of the optimal goodput with respect to the transmit signal-to-noise ratio is found, and the harmfulness of time correlation and the benefit of LOS links are revealed. Finally, the analytical results are validated through extensive simulations.

Multipair Two-Way Full-Duplex Relaying With Massive Array and Power Allocation

We consider a multipair two-way full-duplex relay network, where multiple pairs of full-duplex users can exchange information through a common relay station with a single massive array. Each user has one shared-antenna and the relay station has $M$ shared-antennas. The relay adopts amplify-and-forward protocol, and the beamforming is performed using maximal-ratio combining/transmission or zero-forcing reception/transmission method. When the number of relay antennas grows to infinity or large enough, we derive the asymptotic transmit power of relay and the asymptotic/approximate spectral efficiency with/without power-scaling. The users’ transmit powers are optimally allocated to maximize the spectral efficiency under the users’ total transmit power constraint. Simulations verify our asymptotic and approximate results with large-scale antenna array, and demonstrate the spectral and energy efficiency with optimal power allocation.

Secure Communications for Dual-Polarized MIMO Systems

To enhance secure communications, we deploy the dual-polarized antenna arrays at communication nodes of the multi-input multioutput (MIMO) system, where the base station communicates with multiple legitimate users in the presence of an eavesdropper. We also adopt the dual-structured precoding in which a preprocessing matrix based on the polarized array spatial correlation and a linear precoding based on the instantaneous channel state information (CSI) are concatenated. We design this dual-structured multiuser linear precoding under three cases. In the first case, given perfect global CSI, the secrecy rate optimization problem is formulated and transformed into the weighted minimum mean square error (MSE) problem, which can be effectively solved by the block coordinate decent method. In the second case, where the eavesdropper's CSI is unavailable, an artificial noise is generated to confuse the eavesdropper by minimizing the information transmit power subject to a preset MSE threshold for the recovered confidential signals, which can be solved by an efficient iterative algorithm. In the third case of imperfect global CSI, the robust optimization for secure communications is performed by minimizing the largest received MSE among the users subject to the total transmit power constraint, which can be reformulated into a biconvex semidefinite programming problem and solved by an efficient alternating convex optimization. Simulation results are included to demonstrate the excellent performance of our proposed designs over the conventional single-polarized array-based designs, in terms of achievable secrecy rate, minimum transmit power, and the MSE of recovered confidential signals.

Full-Duplex Regenerative Relaying and Energy-Efficiency Optimization Over Generalized Asymmetric Fading Channels

This paper is devoted to the end-to-end performance analysis, optimal power allocation (OPA), and energy-efficiency (EE) optimization of decode-and-forward (DF)-based full-duplex relaying (FDR) and half-duplex relaying (HDR) systems. Unlike existing analyses and works that assume simplified transmission over symmetric fading channels, we consider the more realistic case of asymmetric multipath fading and shadowing conditions. To this end, exact and asymptotic analytic expressions are first derived for the end-to-end outage probabilities (OPs) of the considered DF-FDR set ups. Based on these expressions, we then formulate the OPA and EE optimization problems under given end-to-end target OP and maximum total transmit power constraints. It is shown that OP in FDR systems is highly dependent upon the different fading parameters and that OPA provides substantial performance gains, particularly, when the relay self-interference (SI) level is strong. Finally, the FDR is shown to be more energy-efficient than its HDR counterpart, as energy savings beyond 50% are feasible even for moderate values of the SI levels, especially at larger link distances, under given total transmit power constraints and OP requirements.

Design of linear precoder for correlated multiuser MIMO system with imperfect CSI

In this paper, we have designed a transceiver to minimize the mean square error (MSE) subject to total transmit power constraint for multi-user multiple input multiple output (MU-MIMO) system under imperfect channel state information (CSI). For the transmission, we presume spatially and temporarily correlated Rayleigh flat fading channel. Because of channel estimation error and feedback delay, the CSI existing at both transmit and receive side will be imperfect. In addition, mutual coupling significantly degrade the system performance. Thus, we also considered the mutual coupling of antenna at both sides of the downlink (DL) which was neglected in previous work. With the above scenario, the proposed precoder design shows significant improvement in bit error rate (BER) compared with the existing precoder model. The linear MMSE prediction algorithm for channel gain is proposed for further progression in performance. The simulation result shows the precoder with predicted CSI results in better BER performance than the existing method. The results are validated by comparing the simulation results with their analytical performance.

Downlink Ergodic Rate Analysis for Virtual Cell Based Cloud Radio Access Networks

Cloud Radio Access Network (CRAN) is a promising approach to cope with the challenges of next generation mobile communications. This paper studies the downlink ergodic rate of a ( $N$ , $K$ ) virtual cell-based CRAN, in which each mobile station (MS) selects the $N$ closest remote radio heads (RRHs) to form its virtual cell and the $K$ ( $K\leq N$ ) closest RRHs will serve the target MS cooperatively with a total transmit power constraint. Using the stochastic geometry, the locations of RRHs and MSs are modeled as two independent Poisson point processes, respectively. Then, a computationally tractable integral expression is derived for the downlink ergodic rate of the ( $N$ , $K$ ) virtual cell-based CRAN. The analytical expression indicates that in the interference limited regime, the ergodic rate only relies on the MS to RRH intensity ratio and is independent with the individual intensity of either the RRH or the MS. Therefore, without deteriorating the downlink ergodic rate significantly, the number of simultaneously served MSs can be improved by increasing the RRH intensity. Specially, when there is only one RRH in each virtual cell, the analytical expression reduces to the ergodic rate expression for the conventional cellular networks. Numerical results indicate that the cooperation among multiple RRHs within each virtual cell can improve the downlink ergodic rate significantly.

Probabilistic Robust Secure Beamforming in MISO Channels With Imperfect LCSI and Statistical ECSI

In this paper, we investigate the robust secure transmit beamformming design for multiple-input single-output wiretap channels overheard by multiple non-collaborating single-antenna eavesdroppers. Assuming that at the transmitter, the instantaneous legitimate receiver’s channel state information (CSI) is imperfect and only the statistical eavesdroppers’ CSI is known, we seek to maximize the target secrecy rate $R$ with the total transmit power constraint and the secrecy outage probability constraint. The resulting outage-constrained secrecy rate maximization (O-SRM) is non-convex and difficult to solve. Thus, we develop an efficient algorithm to solve it and determine the robust secure beamforming design. Specifically speaking, we first prove that the original O-SRM problem can be solved by an equivalent outage-constrained power minimization problem (O-PMP), which is easy to perform semi-definite relaxation (SDR) and can be solved by semi-definite program (SDP) consequently. Second, we transform the non-convex secrecy rate outage constraints into deterministic ones by resorting to Bernstein-type inequality II. Finally, by solving the convex approximation of the O-PMP with different $R\text{s}$ and bisection search over $R$ , we convert the original O-SRM problem into a sequence of solvable SDPs. Simulation results are provided to verify the secrecy-rate performance improvement of the proposed robust beamforming compared with the existing worst-case design proposed by Li and Ma and the simple non-robust maximum-ratio transmission.

Dynamic resource allocation for multimedia services delivery in cellular/infostation integrated HSR networks

With the rapid development of high-speed railway HSR system, the resource allocation problem in HSR wireless network becomes one of the key issues to improve the efficiency of resource utilisation. In this paper, we investigate the downlink resource allocation problem for multimedia services delivery in HSR multiple-input multiple-output MIMO-orthogonal frequency division multiplexing OFDM system with a cellular/infostation integrated network architecture. Taking the train trajectory and network stability into account, we formulate the problem as a stochastic network optimisation programming, which aims at maximising the overall system utility while keeping the system stable under the total transmission power constraint. To address the NP-hard mixed integer programming, the original problem is firstly transformed into a queue stability problem, and then decomposed into two separate subproblems by the drift-plus-penalty DPP approach. Finally, based on the stochastic optimisation technique, a dynamic resource allocation algorithm is proposed and its efficiency is illustrated by theoretical analysis and numerical simulations.

Dynamic resource allocation for multimedia services delivery in cellular/infostation integrated HSR networks

With the rapid development of high-speed railway (HSR) system, the resource allocation problem in HSR wireless network becomes one of the key issues to improve the efficiency of resource utilisation. In this paper, we investigate the downlink resource allocation problem for multimedia services delivery in HSR multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) system with a cellular/infostation integrated network architecture. Taking the train trajectory and network stability into account, we formulate the problem as a stochastic network optimisation programming, which aims at maximising the overall system utility while keeping the system stable under the total transmission power constraint. To address the NP-hard mixed integer programming, the original problem is firstly transformed into a queue stability problem, and then decomposed into two separate subproblems by the drift-plus-penalty (DPP) approach. Finally, based on the stochastic optimisation technique, a dynamic resource allocation algorithm is proposed and its efficiency is illustrated by theoretical analysis and numerical simulations.

Energy and Traffic Aware Full-Duplex Communications for 5G Systems

In this paper, we consider the problem of resource allocation in a dense small-cell network. Each small-cell base station is powered by a renewable energy source and operates in the full-duplex mode. We account for the rate-dependent energy term for data decoding into the total energy consumption at the small-cell base station. Owing to this new energy term, the transmitter and receiver operations now draw the energy from a common source. For a new energy consumption model and high interference scenario, which arises due to full-duplex communications, we formulate an energy and load aware resource management optimization problem under the energy causality and total transmit power constraints of the small-cell base station and uplink user equipments. In particular, the problem minimizes the data queue length of each network user equipment by jointly designing the beamformers, power, and sub-carrier allocation and their scheduling. Owing to the non-convexity of the problem, a global solution is inefficient; thus, we opt for the successive parametric convex approximation method to obtain a sub-optimal solution. This method solves for the convex approximate of the non-convex problem in each iteration and leads to faster convergence. For practical implementation, we further develop a distributed algorithm by using the dual decomposition framework, which relies on limited exchange of information between the involved base stations. Numerical simulations compare the network scenario which accounts for uplink channel rate-dependent energy consumption with that which ignores it. Results advocate the need for redesigning of the resource allocation scheme. In addition, numerical simulations also validate the usefulness of full-duplex communications over the half-duplex communications in terms of minimizing the sum data queue length of the users.

Optimal Signaling for Secure Communications Over Gaussian MIMO Wiretap Channels

Optimal signaling over the Gaussian multiple-input multiple-output wire-tap channel is studied under the total transmit power constraint. A closed-form solution for an optimal transmit covariance matrix is obtained when the channel is strictly degraded. In combination with the rank-1 solution, this provides the complete characterization of the optimal covariance for the case of two transmit antennas. The cases of weak eavesdropper and high SNR are considered. It is shown that the optimal covariance does not converge to a scaled identity in the high-SNR regime. Necessary optimality conditions and a tight upper bound on the rank of an optimal covariance matrix are established for the general case, along with a lower bound to the secrecy capacity, which is tight in a number of scenarios.

Low‐complexity energy‐efficient resource allocation for delay‐tolerant two‐way orthogonal frequency‐division multiplexing relays

Energy-efficient wireless communication is important for wireless devices with a limited battery life and cannot be recharged. In this study, a bit allocation algorithm to minimise the total energy consumption for transmitting a bit successfully is proposed for a two-way orthogonal frequency-division multiplexing relay system, whilst considering the constraints of quality-of-service and total transmit power. Unlike existing bit allocation schemes, which maximise the energy efficiency (EE) by measuring ‘bits-per-Joule’ with fixed bidirectional total bit rates constraint and no power limitation, their scheme adapts the bidirectional total bit rates and their allocation on each subcarrier with a total transmit power constraint. To do so, they propose an idea to decompose the optimisation problem. The problem is solved in two general steps. The first step allocates the bit rates on each subcarrier when the total bit rate of each user is fixed. In the second step, the Lagrangian multipliers are used as the optimisation variants, and the dimension of the variant optimisation is reduced from 2N to 2, where N is the number of subcarriers. They also prove that the optimal point is on the bounds of the feasible region, thus the optimal solution could be searched through the bounds.

Performance Analysis and Power Allocation for Underlay Cognitive MIMO Relaying Networks with Transmit Antenna Selection Under Antenna Correlation

In this paper, we examine transmit antenna selection with receiver maximal ratio combining (TAS/MRC), and selection combining (TAS/SC) in underlay multiple-input multiple-output cognitive relay networks with decode-and-forward relaying protocol, considering optimal and suboptimal cases. The considered secondary user (SU) network consists of a source, a relay and a destination each equipped with multiple correlated antennas. On the other hand, the primary network is composed of L primary users (PU) destinations, each of which is equipped with multiple correlated antennas. The SU transmission power is limited to the minimum between the maximum allowable power for transmission and the maximum interference power allowed by the PU network. In the analysis, all the channel coefficients between the PU and SU networks and between the SU nodes are assumed to follow independent and identically distributed (i.i.d.) Rayleigh fading distribution. Hence, new exact closed-form expressions are derived to study the outage performance of the considered CRN system. Moreover, for the high SNR values, simple asymptotic expressions for the outage probability are obtained to get more insights on the characterization of the achievable diversity orders and coding gains. The impact of antenna correlation on the system outage probability is investigated for special correlation cases. To enhance SU network performance, a power allocation optimization problem is formulated to minimize the SU asymptotic outage probability by optimally distributing the SU power budget between the SU source and SU relay under the constraints of total allowable SU transmission power and maximum allowable PU interference limit. The derived analytical formulas herein are supported by numerical and simulation results to clarify the main contributions. The results show that although the antenna correlation harms the system coding gain, the considered system can still achieve a full diversity order. Also, The results show that although the outage performance of optimal case outperforms the suboptimal case, the optimal case is more complicated compared to the suboptimal one. Moreover, the optimal power allocation solutions enhance the system outage performance compared to equal distribution model.

Optimal Diagonal Power Loading Minimizing Asymptotic Symbol Error Probability for Distributed MIMO Systems With ZF Receivers

In this paper, we consider a distributed multiple-input–multiple-output (D-MIMO) system, where the channel is flat fading and may be correlated, and experiences both small- and large-scale fading. We assume that full knowledge of channel state information (CSI) is available at the receiver and that only the first-and second-order statistics of the channel are available at the transmitter. For such a system with square quadrature amplitude modulation (QAM), an asymptotic symbol error probability (SEP) is derived for the linear zero-forcing (ZF) receiver. Then, we propose an optimal diagonal power loading (PL) strategy that minimizes the dominant term of the asymptotic SEP subject to either a total transmission power constraint when the total power normalization coefficient can be fed back to the transmitter from the receiver or an individual transmission power constraint. A simple closed-form solution is obtained. Computer simulations show that our presented optimal system attains significant performance gains over the currently available equal PL system.

State‐based potential power allocation game in a cooperative multiuser network

Multiuser cooperative communications represent a research area of great interest constituting a key technology for future wireless networks. In this study, the authors consider a scenario of multi-user, single-relay network, where each user employs a part of the relay's transmission power taking into account the constraint of the total transmission power of the relay. The problem of relay power allocation to individual users with a view to optimising the long-term network performance is investigated. An adequate utility function is defined, in terms of outage probability, evaluating the cooperative network's performance due to the relay's cooperation. Taking into consideration the distributed nature of cooperative networks along with the coupled constraint of relay's total transmission power, the specific problem is transformed from a network-level to a user-level optimisation problem using a modern game-theoretic tool. More specifically, the initial power allocation problem is formulated as a state-based potential game for which the corresponding Nash equilibrium exists. Finally, a gradient learning mechanism is proposed to achieve the stationary state Nash equilibrium of the game that constitutes also the global optimal solution of the initial problem. The performance of the new proposed scheme is investigated through numerical simulations for various network parameters.

Power allocation and subcarrier assignment for joint delivery of unicast and broadcast transmissions in OFDM systems

Most existing studies on broadcast services in orthogonal frequency division multiplexing (OFDM) systems have focused on how to allocate the transmission power to the subcarriers. However, because a broadcasting system must guarantee quality of service to all users, the performance of the broadcast service dominantly depends on the channel state of the user who has the lowest received signal-to-noise ratio among users. To reduce the effect of the worst user on the system performance, we propose a joint delivery scheme of unicast and broadcast transmissions in OFDM systems with broadcast and unicast best-effort users. In the proposed joint delivery scheme, the BS delivers the broadcast information using both the broadcast and unicast subcarriers at the same time in order to improve the performance of the broadcast service. The object of the proposed scheme is to minimize the outage probability of the broadcast service while maximizing the sum-rate of besteffort users. For the proposed joint delivery scheme, we develop an adaptive power and subcarrier allocation algorithm under the constraint of total transmission power. This paper shows that the optimal power allocation over each subcarrier in the proposed scheme has a multi-level water filling form. Because the power allocation and the subcarrier assignment problems should be jointly solved, we develop an iterative algorithm to find the optimal solution. Numerical results show that the proposed joint delivery scheme with adaptive power and subcarrier allocation outperforms the conventional scheme in terms of the outage probability of the broadcast service and the sum-rate of best-effort users.

Secure communication design for multi‐user peer‐to‐peer wireless relay networks

In this study, physical layer security techniques are studied for multi-user peer-to-peer relay networks using amplify-and-forward protocol in the presence of an eavesdropper. Two system designs are considered: the minimum achievable secrecy rate maximisation and the total transmit power minimisation. First, considering user fairness, the authors study the max–min achievable secrecy rate problem subject to a total transmit power constraint. Mathematically, the optimisation problem is non-linear and non-convex. They propose a polynomial time algorithm based on the bisection technique to solve it. Second, they study the total transmit power minimisation problem which aims at minimising the total transmit power at relays such that individual secrecy rate for each user is satisfied. The total power optimisation problem is also non-convex, so they use the relaxation technique to transform it into a convex problem which can be efficiently solved by the gradient-based algorithms. Numerical evaluation of the obtained secrecy rate and transmit power results shows that the proposed designs can significantly improve the performance of secure wireless communications.