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Abstract This paper investigates the power allocation in a massive multiple‐input multiple‐output (MIMO) downlink system, where the base station (BS) simultaneously transmits information and energy to information terminals and energy terminals without resorting to any wireless energy harvesting (EH) protocol, respectively. First, with respect to this system, the closed‐form expressions of achievable rate and harvested energy are, respectively, derived for Rayleigh fading channels. Then, from these expressions, three optimization problems are formulated based on quality‐of‐service (QoS) requirements, with the purposes of maximizing achievable sum rate, harvested sum energy and joint QoS requirements, respectively. The optimization problem of maximizing achievable sum rate is transformed into a sequence of geometric programmings (GPs), which can be solved efficiently with standard convex optimization tools. The optimization problem of maximizing harvested sum energy is proved to be solvable as a linear program. The optimization problem of maximizing joint QoS requirements is shown to be a multi‐objective optimization problem (MOOP) and solved by a one‐dimensional search based on GP. Finally, numerical results manifest that the proposed power allocation algorithms can provide good system performances of achievable sum rate and harvested sum energy, and jointly guarantee QoS fairness in terms of achievable rate and harvested energy.

Abstract Secure transmission is essential for future non-orthogonal multiple access (NOMA) system. This paper investigates relay–antenna selection to enhance physical-layer security of cooperative NOMA system in the presence of an eavesdropper, where multiple antennas are deployed at the relays, the users, and the eavesdropper. In order to reduce expense on radio frequency chains, selection combining (SC) is employed at both the relays and the users, whilst the eavesdropper employs either maximal-ratio combining or SC to process the received signals. Under the condition that the channel state information of the eavesdropping channel is available or unavailable, two effective relay–antenna selection schemes are proposed. Additionally, the closed-form expressions of secrecy outage probability (SOP) are derived for the proposed relay–antenna selection schemes. In order to gain more deep insights on the derived results, the asymptotic performance of the derived SOP is analyzed. In simulations, it is demonstrated that the theoretical results match well with the simulation results and the SOP of the proposed schemes is less than that of the conventional orthogonal multiple access scheme obviously.

Abstract Both cooperative non‐orthogonal multiple access (NOMA) and physical layer security (PLS) are promising techniques for future communication systems. This paper investigates the PLS performance of a cooperative NOMA system where multiple sources transmit a superposed message to two users by utilizing either amplify‐and‐forward (AF) or decode‐and‐forward (DF) relays in both non‐colluding and colluding eavesdropper scenarios. A source‐relay selection scheme is proposed for this system aiming at improving the secrecy performance. Additionally, the closed‐form expression of the secrecy outage probability (SOP) is derived for the proposed source‐relay selection schemes. It is demonstrated that in the proposed schemes, the theoretical results match well with the simulation results. In addition, the proposed schemes outperform the conventional OMA system in terms of SOP.

Abstract This paper investigated the spectral efficiency (SE) in massive multiple-input multiple-output systems, where all terminals have no fixed power supply and thus need to replenish energy via the received signals from the base station. The hybrid wireless energy harvesting (EH) protocol is applied for each terminal, which can switch to either existing time-switching (TS) protocol or power-splitting (PS) protocol. Based on the hybrid wireless EH protocol, a general system model is developed, which can switch to either only uplink data transmission or only downlink data transmission. As a result, a general analytical framework is formulated. Then, closed-form lower bound expressions on SE for each terminal are obtained on the uplink and downlink, respectively. According to these expressions, the joint SE of uplink and downlink maximization problem is designed with some practical constraints. As the designed optimization problem is non-linear and non-convex, it is hard to solve directly. To provide a solution, an iteration algorithm is proposed by utilizing one-dimensional search technique and successive approximation method based on geometric program. Additionally, the convergence and complexity of the proposed algorithm are discussed as well. Finally, the feasibility of the proposed algorithm is analyzed by simulations. Numerical results manifest that the proposed algorithm can provide good SE by optimizing relevant system parameters, and the system model can help to discuss the TS, PS or hybrid protocol for only uplink data transmission, only downlink data transmission or joint data transmission of uplink and downlink in the considered system.

Abstract This paper considers a relay‐assisted massive multiple‐input multiple‐output (MIMO) downlink system in which a base station (BS) communicates with all terminals via a relay node enabled simultaneous wireless information and power transfer (SWIPT). Both time‐switching (TS) and energy‐splitting (PS) protocols are respectively considered at the relay node for coordinating energy harvesting and information decoding. The quality‐of‐service (QoS) fairness problem among terminals is investigated in the considered systems. In detail, the power allocation coefficients and energy harvesting time duration for TS based SWIPT, and the power allocation coefficients and PS ratio for PS based SWIPT are jointly optimised, aiming at seeking to maximise the minimum achievable rate over all terminals. As the formulated problems are non‐convex and non‐linear, and hard to solve directly, suboptimal heuristic algorithms are proposed for solving them. Additionally, the convergence and complexity of the proposed algorithms are also analysed. Finally, the performance of the proposed algorithms is demonstrated by extensive computer simulations. Results manifest that the proposed algorithms can provide uniformly great QoS for every terminal by resource allocation.

Abstract The paper investigates simultaneous wireless information and power transfer (SWIPT) in massive distributed antenna systems, where the remote radio heads (RRH) equipped with a large number of antennas are arbitrarily distributed over the coverage area and each terminal operates via a power‐splitting (PS) device. Utilising the harvested energy, each terminal transmits its pilot signals for channel estimation. A closed‐form lower bound expression on the downlink ergodic capacity is derived for each terminal and then downlink ergodic sum capacity maximisation problem with respect to RRH‐terminal association, channel estimation duration, PS ratios and power allocation (PA) is designed. The designed problem is proved to be a mixed‐inter nonlinear programming with combinatorial variables, which is generally hard to solve due to its NP‐hardness. To this end, a hierarchical iterative algorithm is developed by utilising decomposition technique. Moreover, the convergence and computational complexity of this algorithm are analysed as well. Numerical results manifest the feasibility and effectiveness of this algorithm, and also show that it can achieve the maximum downlink ergodic sum capacity for massive distributed antenna systems with SWIPT protocol.