The pinching-antenna system (PASS) reconfigures wireless links through pinching beamforming, in which the activated locations of pinching antennas (PAs) along dielectric waveguides are optimized. This article investigates the application of PASS in multicast communication systems, where pinching beamforming is designed to maximize the multicast rate. i) In the single-waveguide scenario, a closed-form solution for the optimal activated location is derived under the assumption of a single PA and linearly distributed users. Based on this, a closed-form expression for the achievable multicast rate is obtained and proven to be larger than that of conventional fixed-location antenna systems. For the general multiple-PA case with arbitrary user distributions, an element-wise alternating optimization (AO) algorithm is proposed to design the pinching beamformer. ii) In the multiple-waveguide scenario, an AO-based method is developed to jointly optimize the transmit and pinching beamformers. Specifically, the transmit beamformer is updated using a majorization-minimization (MM) framework together with second-order cone programming (SOCP), while the pinching beamformer is optimized via element-wise sequential refinement. Numerical results are provided to demonstrate that: i) PASS achieves significantly higher multicast rates than conventional fixed-location antenna systems, particularly when the number of users and spatial coverage increase; ii) increasing the number of PAs further improves the multicast performance of PASS.

This article addresses the design of multigroup multicast communications in the pinching-antenna system (PASS). A PASS-enabled multigroup transmission framework is proposed to maximize multicast rates under a couple of transmission architectures: waveguide-division (WD) and waveguide-multiplexing (WM). 1) For WD, an element-wise sequential optimization strategy is proposed forpinching beamforming, i.e., optimizing the activated positions of pinching antennas along dielectric waveguides. Meanwhile, a log-sum-exp projected gradient descent algorithm is proposed for transmit power allocation across waveguides. 2) For WM, a majorization-minimization (MM)-based framework is proposed to tackle the problem’s non-smoothness and non-convexity. On this basis, a low-complexity element-wise sequential optimization method is developed for pinching beamforming using the MM surrogate objective. Furthermore, the optimal transmit beamformer structure is derived from the MM surrogate objective using the Lagrange duality, with an efficient transmit beamforming algorithm proposed using projected adaptive gradient descent. Numerical results demonstrate that: i) both WD and WM architectures in PASS achieve significant multicast rate improvements over conventional MIMO techniques, especially for systems with large service areas; ii) WM is more robust than WD in dense deployments, while WD excels when user groups are spatially separated.

This article investigates secure multicast communications in pinching-antenna systems (PASS), where pinching beamforming is enabled by adaptively adjusting pinching antenna (PAs) positions along waveguides to improve multicast security. Specifically, a PASS-based secure multicast framework is proposed, in which joint optimization of transmit and pinching beamforming is conducted to maximize the secrecy multicast rate. i) For the single-group multicast scenario, an alternating optimization (AO) framework is employed, where the pinching beamformer is updated via an element-wise sequential optimization method. The transmit beamformer is designed via a semidefinite relaxation (SDR) formulation for an upper-bound solution, while a Dinkelbach-alternating direction method of multipliers (ADMM) offers a low-complexity alternative. ii) For the multi-group multicast scenario, transmit and pinching beamformers are alternately optimized under a majorization-minimization (MM) framework. The transmit beamformer is obtained via SDR or an efficient second-order cone programming (SOCP) method, while the pinching beamformer is updated through MM-based element-wise sequential update strategy. Numerical results are provided to demonstrate that: (i) PASS consistently outperform conventional fixed-location antenna architectures in terms of secrecy performance across various configurations; and (ii) the performance advantage of PASS over fixed-location architectures becomes more significant with increased service region, larger antenna arrays, and higher user and eavesdropper densities.

This paper studies the application of pinching-antenna systems (PASS) in multicast communications. The minimum-rate maximization problem is formulated, and both single-pinching antenna (PA) and multiple-PA deployment over a single waveguide are considered. 1) For the single-PA scenario, a closed-form solution is derived for one-dimensional user distributions, and a candidate-point search strategy is proposed for arbitrary user placements. 2) For the multiple-PA scenario, the pinching beamforming is optimized through a low-complexity greedy search approach. Numerical results demonstrate that: i) PASS achieves a higher multicast rate compared to conventional fixed-antenna systems; ii) the proposed approaches substantially reduce computational complexity compared to traditional exhaustive search algorithms.

The technique of digital twin network (DTN) has been considered as a promising technique of network management and control to accommodate disruptive applications for the sixth generation communication (6G) systems. However, it is still challenging for DTN to provide ultimate experience for the emerging services and applications, due to the lack of effective DTN model management strategies. To solve this problem, the model selection and offloading for DTN is studied in this paper. First, a framework of cooperative model selection and offloading for DTN is designed, which can adapt with the limited computation capability of users, and improve the communication efficiency of model offloading. Second, the performance metrics are proposed to effectively evaluate the accuracy loss and the privacy leakage risk of model management for DTN, and tractable expressions are provided for our studied framework. Third, a joint optimization algorithm is designed for model management and transmit power allocation, which can efficiently reduce the accuracy loss and the privacy leakage risk with low processing latency. Finally, the experiment results are provided to show the effectiveness of our introduced performance metrics, and verify the performance gains of proposed optimization algorithm for our studied framework.

Cognitive radio (CR) and integrated sensing and communication (ISAC) are both critical technologies for the sixth generation (6G) wireless networks. However, their interplay has yet to be explored. To obtain the mutual benefits between CR and ISAC, we focus on a reconfigurable intelligent surface (RIS)-enhanced cognitive ISAC system and explore using the additional degrees-of-freedom (DoFs) brought by the RIS to improve the performance of the cognitive ISAC system. Specifically, we mathematically prove that the position error bound (PEB) of each mobile sensor (MS) decreases with the increasing signal-to-noise ratio (SNR) of the received signals at each MS. We also formulate an optimization problem of maximizing the signal-to-noise-plus-interference ratios (SINRs) of the MSs while ensuring the requirements of the spectrum sensing (SS) and the secondary transmissions by jointly designing the SS time, the secondary base station (SBS) beamforming, and the RIS beamforming. The formulated non-convex problem can be solved by the proposed block coordinate descent (BCD) algorithm based on the Dinkelbach’s transform and the successive convex approximation (SCA) methods. Simulation results demonstrate that all the proposed iterative algorithms converge fast, and the SINRs of MSs can be effectively enhanced by increasing the transmit power of the SBS, the number of MS antennas, and the number of RIS elements. Moreover, higher MS SINRs lead to lower PEBs of MSs, thereby having the potential to improve the accuracy of radio environment map (REM) for CR networks. Additionally, the RIS needs to be deployed near the SBS or MSs to guarantee the performance gain brought by the RIS.

Integrated sensing and communications (ISAC) is an emerging technique for the next generation of communication systems. However, due to multiple performance metrics used for communication and sensing, the limited number of degrees-of-freedom (DoF) in optimizing ISAC systems poses a challenge. Reconfigurable intelligent surfaces (RISs) can introduce new DoF for beamforming in ISAC systems, thereby enhancing the performance of communication and sensing simultaneously. In this paper, we propose two optimization techniques for beamforming in RIS-assisted ISAC systems. The first technique is an alternating optimization (AO) algorithm based on the semidefinite relaxation (SDR) method and a one-dimension iterative (ODI) algorithm, which can maximize the radar mutual information (MI) while imposing constraints on the communication rates. The second technique is an AO algorithm based on the Riemannian gradient (RG) method, which can maximize the weighted ISAC performance metrics. Simulation results verify the effectiveness of the proposed schemes. The AO-SDR-ODI method is shown to achieve better communication and sensing performance, than the AO-RG method, at a higher complexity. It is also shown that the mean-squared-error (MSE) of the estimates of the sensing parameters decreases as the radar MI increases.

High throughput satellite (HTS) has been identified as a key technology for improving communication capacity of satellite system. Recently, low earth orbit high throughput satellite (LEO-HTS) has attracted much attention because of its low latency and construction cost. However, LEO-HTS is power-limited when it passes through the shadow of the earth, which will affect the lifetime and capabilities of the satellite. This paper focuses on the problem of energy saving for multiple LEO-HTSs in the LEO-HTS constellation. A method of adaptive power allocation with multi-beam directivity control according to the traffic demand of user equipments (UEs) is proposed to save energy. In this case, an optimization model is established to minimize the transmission power of multiple LEO-HTSs. Then, an alternating optimization framework is introduced to iteratively solve the transmission power and multi-beam directivity of multiple LEO-HTSs. Finally, numerical results demonstrate that the proposed method can save energy more effectively than the traditional method in the scenario with high traffic demand and concentrated UE distribution.

The reconfigurable intelligent surface (RIS) is regarded as a promising technology for the future networks, since it has the ability to manipulate the randomly behaving wireless communication environment. However, due to the large number of the passive RIS elements, the pilot overhead of channel estimation in the RIS-assisted communication system is huge. To address this issue, we propose a three-step orthogonal matching pursuit (OMP) based algorithm which can further improve the channel estimation accuracy compared to the existing pilot-saving schemes. The proposed algorithm can overcome the effect of noise by expanding the number of training samples for the estimation of the same channel parameters. Specifically, the joint sparsity structure of the cascaded channels associated with different users is fully revealed and exploited in this paper. Based on this sparsity structure, the classical OMP algorithm is modified to jointly estimate channel parameters. Simulation result shows that, to achieve the same channel estimate accuracy, the pilot overhead of channel estimation of the proposed algorithm is lower than the existing schemes.

Intelligent reflection surface (IRS) has been identified as a promising technology for improving the performance of wireless communication systems. This paper focuses on the downlink scenario of an IRS-enhanced multi-user multiple-input single-output system. However, the channel state information (CSI) of the channels associated with IRS is difficult to estimate due to the passive feature of IRS. Meanwhile, the ideal continuous phase shifts of IRS elements are challenging to obtain owing to the hardware imperfection. This paper establishes an optimization model to minimize the base station (BS) transmit power subject to the discrete phase shifts of IRS and the weighted sumrate outage probability, which takes into account the practical statistical CSI error. We first apply the decomposition-based large deviation inequality to safely approximate the weighted sum-rate outage probability since the closed form expression of outage probability is hard to obtain. Then, the alternating optimization framework is introduced to iteratively solve the joint BS and IRS beamforming. In particular, the negative square penalty method is used to solve the non-convex sub-problem, i.e., the IRS passive beamforming. Numerical results demonstrate the effectiveness of the proposed algorithm.

High-speed train (HST) communication has become one of the standard communication scenarios, due to the rapid development of HST techniques. Many researchers have been focusing on it recently. This paper discusses the reproduction of HST channels in laboratory environments, via carrying out an over-the-air (OTA) testing campaign. We conducted measurement work in practical railway environments, and established a non-stationary geometry-based stochastic channel model according to the measured data. Moreover, an OTA testing campaign was performed based on the multi-probe anechoic chamber (MPAC) method. The testing results suggest that great matches have been achieved between the indicators recorded in laboratory and the measured ones in railway environment, e.g., reference signal receiving power (RSRP), Doppler frequency spectrum (DFS) and power delay profile (PDP).

A dilemma in cloud radio access networks (C-RANs) is how to keep a balance between the performance and the efficiency of centralized processing. To solve this problem, the joint design of channel estimation and cluster formation are studied in this paper. In particular, a data-assisted channel estimation scheme is used to reduce the redundant cost of training sequences, and C-RAN clusters are formed by the remote radio heads (RRHs) to provide efficient cooperation strategies. To ensure the performance of channel estimation and data transmission, the cluster formation and the channel estimation are optimized jointly. An iterative channel estimation scheme is designed by using convex optimization and the Broyden-Fletcher- Goldfarb-Shanno (BFGS) algorithm jointly. Moreover, a utility function of cluster formation can be established based on the estimates and the mean squared error (MSE) of our proposed channel estimation algorithm, and the cluster formation of RRHs can be formulated as a coalitional formation game. Finally, the simulation results are shown to evaluate the performance of our proposed algorithms.

A key problem of content caching networks is that extra radio resource blocks are consumed to push content objects, which leads to a decline of spectrum efficiency. To solve this problem, a non-orthogonal multiple access-based multicast (NOMA-MC) scheme is proposed in this paper, where pushing and multicasting content objects can be accomplished simultaneously, and thus the spectrum efficiency can be improved significantly. To evaluate the performance of the NOMA-MC scheme, an explicit expression of outage probability is derived, which shows that full diversity gains can be achieved in the single-cell scenario. Moreover, the theoretical results can be extended to the multi-cell scenario by establishing a stochastic geometry-based network model, which show that the NOMA-MC scheme can achieve better performance than the conventional orthogonal multiple access-based multicast scheme. Then, the joint design of power allocation and content matching is studied to enlarge the performance gains of the NOMA-MC scheme, and two distributed optimization algorithms are proposed by solving a hospitals/residents matching problem. Finally, simulation results are provided to verify the analytical results, and also demonstrate the performance gains of the NOMA-MC scheme.

Cloud-radio access networks (C-RANs) are considered as energy efficient network architectures. Nevertheless, a dilemma in C-RAN architecture is to simultaneously optimize both spectral efficiency (SE) and energy efficiency (EE). In this paper, the tradeoff between SE and EE are studied considering a downlink multicasting transmission scenario in a C-RAN. In particular, to effectively mitigate the severe interference caused by densely deployed RRHs and improve the energy efficiency, a thinning scheme of RRHs is proposed. With a fixed diluted density of deployed active RRHs, the explicit closed-form expressions for coverage probability, SE and EE are derived by applying stochastic geometry. By using the obtained theoretical result as a utility function, a problem of optimizing the selection radius of RRHs is formulated to make a tradeoff between SE and EE for different preferences. Then, scalarization methods are proposed to give efficient solution. Numerical results validate the correctness and precision of performance analysis and show that the proposed approaches can generate an optimal selection radius of the thinning scheme.

A multi-carrier one-way relay network is considered, in which a source wishes to send information to a destination via a full-duplex amplify-and-forward relay. We perform power allocation across different subcarriers for the source and the relay, as well as subcarrier pairing at the relay, so as to maximize the achievable sum rate subject to individual power budget constraint at each transmit node, and therefore formulate the joint power allocation and subcarrier pairing optimization problem. Due to the interdependency in the power allocation between self-interference subcarrier and outgoing subcarrier at the relay node, we propose a suboptimal scheme to trade the performance for computational complexity. Then dual decomposition technique is employed for power allocation, while the subcarrier pairing problem is solved by Hungarian algorithm. Simulation results show that the proposed resource allocation scheme can significantly improve system performance.

To guarantee the rapidly increasing applications of electrical consumer, ultra small cells have been proposed to provide high spectral efficiency. However, which are severely constrained by the inter-cell interference (ICI) when the system load is high, and the enhanced inter-cell interference coordination (eICIC) is key to improving performance. To quantify the performance gains from eICIC to the load-varied small cells, a stochastic-geometry model is established in this paper, and the successful coverage probability with a dynamic frequency resource allocation (DFRA) scheme adaptive to the varied system load is researched, in which the small cell base station (SCBS) location is modeled as a Poisson point process. The proposed DFRA scheme can decrease ICI through the cooperation of adjacent SCBSs, which results in the correlated spectral usage in adjacent SCBSs. Several approximations are used to handle this kind of correlation, and a Bayesian theory based evaluation method is proposed to derive the asymptotic expression of successful coverage probability. Simulation results show that these approximated expressions match well with the simulated results, and the proposed DFRA can effectively decrease ICI and significantly increase the success coverage probability.

In cognitive radio networks, primary users can share some licensed spectrums with secondary users in exchange for cooperation. In this study, an overlay scenario is investigated where a secondary node provides two‐way relaying service to a pair of primary users and thus is allowed to transmit its own messages by using some licensed spectrums. Orthogonal channelisation is assumed for the two‐way relay channel to form a number of parallel subchannels. Hence, the licensed spectrums can be partitioned between primary and secondary signals transmitted by the relay in the broadcast phase. Moreover, subchannels in the two phases of two‐way relaying can be permutated to further improve performance. The authors seek to maximise achievable data rate of secondary transmission subject to data rate requirements of the two primary users under individual power constraints. The joint spectrum partition, subchannel permutation, and power allocation problem is formulated into a mixed combinatorial programming problem, which is then transformed into a solvable form and finally yield an asymptotically optimal solution through dual decomposition method. They further prove that the solution to the relaxed problem is exactly the same as that to the original problem. Numerical results demonstrate performance gain of the proposed algorithm.

Relay power control for two-way (TW) full-duplex (FD) relay network is studied in this letter. In the prior literature, the relay is assumed to always use its full transmit power in a TW FD relay network. However, high transmit power will increase loopback self-interference at the relay node and thus make the incoming link to the relay become the bottleneck for the end-to-end performance. Therefore, it is suboptimal to always utilize the full power capability of the relay. Thus, we propose three relay power control schemes, which can, respectively, maximize 1) the data rate of an individual end node, 2) the minimum data rate of the two end nodes, and 3) the sum data rate of the two end nodes. Numerical results show that, compared to using full relay power, the proposed relay power control schemes can improve system performance while reducing relay power consumption.

An optimal resource allocation scheme for orthogonal frequency division multiplexing (OFDM) based multiuser two-way full duplex (FD) relaying is discussed in this paper. Compared with traditional half duplex (HD) relaying, FD mode can double data rate under perfect interference cancellation, which, however can not be achieved under realistic conditions. Our goal is to maximize the throughput of the whole system by allocating available power and subcarriers under residual self-interference. We formulate a nonlinear optimization problem under individual power constraints. An optimal solution is obtained by using Lagrange dual decomposition method. In addition, a suboptimal solution which reduces the computational complexity significantly is also provided in this paper. Numerical results indicate advantage of the optimal resource allocation scheme proposed in this paper.

Considering that full-duplex relaying (FDR) can achieve higher spectral efficiency than traditional half-duplex relaying (HDR), a spectrum sharing protocol based on FDR is proposed in this paper. We investigate a two-phase FDR spectrum sharing protocol in cognitive two-way relay networks. Analytical expressions for the outage probabilities of the primary and secondary systems under the proposed protocol are derived in a closed form. Monte-Carlo simulations are carried out to confirm the analytical expressions. Results show that the performance of our two-way FDR spectrum sharing protocol depends on the residual loop interference (LI) at the relay node. When the residual LI is small, the proposed FDR spectrum sharing protocol can significantly improve the outage performance. Furthermore, if the residual LI is small enough, the two-way FDR spectrum sharing scheme can outperform its HDR counterpart, both for the primary system and the secondary system.

Distributed base station caching is an efficient way to reduce the network traffic load in advanced cellular networks, but suffers from a significant network delay due to the multi-hop transmission, leading to a poor quality of service. The presence of a few shortcut direct links transforms a regular network to a small world network resulting in achieving properties of high clustering coefficient and low average path length. In this paper, we propose a delay-optimized small world model for base station caching network to reduce the average network delay by decreasing multi-hop distance. In particular, we first study the degree-based and closeness-centrality shortcut addition strategies. To enhance these two strategies, we propose the delay-optimized shortcut addition strategy to decrease average network delay. The numerical results show that the proposed delay-optimized small world model can reduce the average network delay under remaining the clustering coefficient. Meanwhile, the average network delay with the proposal is 31.26% lower than that with the degree-based strategy, and is 18.78% lower than that with the closeness-centrality strategy.

The simultaneous wireless transfer of information and power with the help of a relay equipped with multiple antennas is considered in this letter, where a “harvest-and-forward” strategy is proposed. In particular, the relay harvests energy and obtains information from the source with the radio-frequent signals by jointly using the antenna selection (AS) and power splitting (PS) techniques, and then the processed information is amplified and forwarded to the destination relying on the harvested energy. This letter jointly optimizes AS and PS to maximize the achievable rate for the proposed strategy. Considering that the joint optimization is according to the non-convex problem, a two-stage procedure is proposed to determine the optimal ratio of received signal power split for energy harvesting, and the optimized antenna set engaged in information forwarding. Simulation results confirm the accuracy of the two-stage procedure, and demonstrate that the proposed “harvest-and-forward” strategy outperforms the conventional amplify-and-forward (AF) relaying and the direct transmission.

The base station (BS) density configuration is a key factor to improve energy efficiency (EE) performances. In this paper, BS density configurations for achieving the optimal EE performance in two-tier cellular networks are analyzed, where the Poisson point process (PPP) is used to model the BS spatial distribution. To make the EE performances trackable and analyzable, the BS density optimization in each tier is transformed into an equivalent problem that jointly optimizes "the sum and the ratio of BS densities". This equivalent optimization problem is not necessarily convex, while its monotonicity with different power consumptions of BSs is analyzable. Considering the optimal BS density configuration is not unique and the closed-form solution for achieving the best EE performance is extremely difficult to be derived, a dynamic gradient based iterative algorithm by solving the quadratic functions is proposed. Furthermore, the quantitative analysis of EE performances based on the data fitting method shows that the approximately linear relationship between the optimal BS density and the user density holds only under specific conditions. Simulation results have demonstrated the effectiveness of the proposed algorithm and verified relevant conclusions.

Spectrum sharing for cognitive two-way relaying is considered in this paper. A secondary relay is used to assist two-way communications between two primary users, and as a return, the secondary relay is allowed to transmit its own secondary signal by using some of the licensed primary spectrum. Three different spectrum sharing strategies are studied in this paper. In the baseline superposition coding (SC) strategy, the relay superimposes its secondary signal on the relayed primary signals in the same phase, and in the SC strategy with secondary interference cancellation (SC-SIC), the interference from the superimposed secondary signal on the primary signals can be removed; whereas in the time division (TD) strategy, the relay uses two distinct phases to transmit the relayed primary signals and its own secondary signal. Therefore, relay power or transmission time is treated as the shared resource and needs to be allocated between primary and secondary transmissions in the three strategies. We develop resource allocation results which can minimize outage probability of the secondary signal, and meanwhile, can satisfy data rate targets of the two primary users. Our results show that, although the SC-SIC strategy requires the least shared resource to achieve the data rate target for primary users, the TD strategy can provide the best performance for secondary transmission because it can completely avoid mutual interference between primary and secondary signals.

Cognitive two-way relaying is studied in this paper. A secondary relay is used to assist bidirectional communication between a pair of primary users. As a return, the secondary relay is allowed to transmit its own secondary signal on the licensed primary spectrum. For this purpose, superposition coding is employed at the relay to superimpose the secondary signal on the primary signals. Three typical cognitive two-way relaying strategies are considered in this paper, namely, amplify-andforward (AF), XOR- based decode-and-forward (DF-XOR) and superposition based DF (DF-SUP). Outage probabilities of the two primary users under these three strategies are derived for Rayleigh fading channels. Their performances are compared with direct transmission and another recently proposed cognitive two-way relaying strategy which enables interference cancelation of the secondary signal at the primary users. Our results show that a major portion of relay power has to be allocated for relaying primary signals because the superimposed secondary signal always plays as an interference to the primary signals. Finally, we propose several potential solutions to suppress this interference to enhance the performance of cognitive two-way relaying.

In this paper, we study a cognitive two-way relay network in which orthogonal frequency division multiplexing (OFDM) technique is adopted within the secondary system and a pair of secondary source nodes communicate with each other through a relay node by using amplify-and-forward two-way relaying strategy. We propose an optimal power allocation scheme to maximize the smaller data rate of the secondary users while satisfying both individual node power and aggregation interference constraints. We decompose the optimization problem into two subproblems and solve them by using dual decomposition approach. Furthermore, we propose a distributed power allocation algorithm. Finally, numerical simulations and comparisons are presented to illustrate the performance of the proposed scheme.

Power allocation for orthogonal frequency division multiplexing (OFDM) based two-way relay link in cognitive relay networks is discussed in this paper. Two secondary source nodes exchange their information through a secondary relay node by using amplify-and-forward two-way relaying strategy. The goal of power allocation is to maximize the sum data rate of the secondary system subject to the constraint that the aggregation interference of the secondary system on the primary system does not exceed the given threshold. In addition, individual node power constraint is applied for both secondary source nodes and the secondary relay node. We solve the optimization problem by using dual decomposition approach, and further propose a distributed power allocation algorithm. Numerical results demonstrate the advantage of the proposed algorithm over uniform power allocation. Besides, power-constrained as well as interference-constrained regions are shown in our numerical experiments.

Joint scheduling and resource allocation in uplink orthogonal frequency division multiplexing (OFDM) systems is complicated, and even gets intractable with large subcarrier and user number. This paper investigates the resource allocation for OFDM-based multi-user multiple-access relay channels (MARC) with network coding. We formulate a joint optimization problem considering source pairing, subcarrier assignment, subcarrier pairing and power allocation to maximize the sum-rate under per-user power constraint. The problem is addressed in polynomial time by optimizing three separate subproblems, and afterwards three low-complexity suboptimal algorithms are further proposed. The simulation results demonstrate performance gain of the proposed algorithms versus per-node transmit power and source nodes number, respectively.

Spectrum sharing between primary and secondary systems in cognitive two-way relay networks is discussed in this paper. A two-phase spectrum sharing protocol is proposed, in which a secondary (cognitive) user acts as the relay to assist the bidirectional primary transmission. Analog network coding (ANC) is employed for two-way relaying between the two primary users, and spectrum sharing is achieved by superimposing the secondary signal on the network-coded primary signals at the secondary relay. We analytically derive the outage probability of the primary users under our proposed two-phase protocol, and identify the spectrum sharing regions within which the spectrum sharing protocol can achieve higher (or at least equal) outage performance for the primary users than direct transmission without spectrum sharing. Results show that our proposed two-phase spectrum sharing protocol can outperform another recently proposed three-phase protocol which is based on decode-and-forward (DF) network coding operation.

Carrier aggregation (CA) has been proposed within 3GPP to aggregate multiple component carriers (CCs) in LTE-Advanced system to achieve higher peak data rate. In this paper, we propose CA between FDD and TDD carriers in order to utilize FDD and TDD spectrums more efficiently. By comparing the differences in control channel between LTE FDD and TDD specifications, three problems in the case of CA between FDD and TDD carriers are identified, and we then propose the respective solutions and analyze their pros and cons. It is shown that CA between FDD and TDD carriers can provide system flexibility and performance benefits for the operators which own both FDD and TDD spectrums.

This paper proposes the separate-SMDP approximation technique to solve the dimensionality problem of the semi-Markov decision process (SMDP) model for radio resource management (RRM). The proposed separate-SMDP model approximates the original complex SMDP linear programming (LP) problem by building a series of simple SMDP LP problems. The estimated policy results are obtained by solving these LP problems in a distributed manner. Related algorithms are proposed to support the model in actual HWN RRM process. This technique not only greatly decreases the computational complexity of SMDP and solves its dimensionality problem, but also adapts well to actual RRM and provides a new horizon for utilizing SMDP.

We consider two end users which have asymmetric traffic requirements in terms of both data rate and outage probability. They exchange information in Rayleigh flat-fading channels, and a half-duplex relay node is employed to assist the bidirectional communication between them, using the analog network coding (ANC) protocol. The provision of power levels for each node is investigated so as to minimize the total energy consumed to satisfy the asymmetric traffic requirements. By comparing energy consumptions between ANC strategy and direct transmission strategy, the relay operating region is also identified in which relay-assisted transmission can yield higher energy efficiency than direct transmission. It also indicates that the relay node is best positioned at the middle point of the two end nodes for any asymmetric traffic requirements from the perspective of energy consumption minimization.

In time division-high speed packet access plus (TDHSPA+) system, multiple input multiple output (MIMO) technique is adopted to improve spectrum efficiency and transmission reliability. However, most current literature are focused on the large spacing antenna setup, which is impractical for user equipment (UE) because of the size limitation. Therefore, dual polarization antenna scheme is introduced in the system to provide multiplexing gain and/or diversity gain. In this paper, we derive the dual polarization channel model for performance evaluation. Furthermore, the performance of dual polarization scheme under different MIMO architectures is presented and analyzed. It is shown that polarization scheme can achieve similar average throughput and successful transmission ratio compared with spatial separation scheme in various scenarios.

Wireless cooperative relay is an efficient way in obtaining diversity in distributed manner, and it can also be used as a way in extending the cell coverage in cellular systems. In this paper, assuming receiver channel state information (CSI) only, the ergodic and outage capacity analysis are presented for amplify-and-forward (AF) multiple-input multiple-output(MIMO) relay channels deploying orthogonal space-time block codes (OSTBCs). Under flat Rayleigh fading environment, we derive closed-form analytical expressions for the calculation of the ergodic capacity and outage capacity for both the OSTBC transmission with and without the direct link. Numerical results show that all the derived analytical expressions are very tight and are valid for evaluations of the ergodic and outage capacity under various antenna configurations. The results also show how the number of transmit antennas and receives antennas affect the overall channel capacity under fading channel environments.

In the next generation wireless systems, it's quite likely that a large number of user terminals are not able to transmit and/or receive over the entire system bandwidth, as much wider system bandwidth, e.g., 100 MHz, is expected to be employed in the future. As a new and challenging problem, user terminal bandwidth limitation is considered in this paper, and multiuser resource allocation for orthogonal frequency division multiplexing (OFDM) downlink with terminal bandwidth limitation is discussed. The optimal multiuser resource allocation strategy is first presented; however, due to the prohibitive computational expense of the optimal strategy, two suboptimal resource allocation strategies with significantly reduced complexity are proposed as well. The performance of the two suboptimal strategies is given via simulations, and is discussed for various scenarios.

Although the established capacity results for the classic three-node relay channel rely on the assumption of fullduplex relay nodes, it's practically difficult for radio transceivers to support simultaneous signal transmission and reception. Timedivision half-duplex relay strategies have thus been proposed to address this limitation. Amplify-and-forward (AF) and decode-and-forward (DF) are two well-known half-duplex relay strategies in the literature. Later, DF approach was extended by the so-called variable-rate two-phase relay strategy, in which the transmission rates for both phases are not necessarily the same. More recently, a novel half-duplex relay strategy based on the information theoretical concepts of broadcast channel (BC) and multiple access channel (MAC) models is proposed. In this approach, the source broadcasts distinct data flows to the destination and the relay respectively during the first phase, and in the second phase the relay forwards the received information whereas the source sends another data flow to the destination. In this paper, we will first develop optimal resource allocation, in terms of power and time, for these half- duplex relay strategies, and then compare their performance under various link conditions.

Hybrid automatic repeat request (HARQ) protocol typically operates in multi-process stop-and-wait (SAW) mode to fully utilize channel capacity. A prior packet, due to retransmission(s), may arrive at the receiving side later than the packets that follow it but use other HARQ processes, thus leading to out-of-order reception. Medium access control (MAC) layer is responsible for packet reordering operations so as to offer in- sequence delivery to upper layer. An arriving packet should be temporarily stored in the reordering buffer, if there is at least one prior packet that has not arrived yet. Nevertheless, protocol stalling may occur if a packet is discarded at the transmitter due to excessive failed retransmissions, or if a negative acknowledgement (NACK) signal is inversed as an acknowledgement (ACK). A timer-based mechanism is suggested by 3GPP to handle protocol stalling. In this paper, we propose an adaptive timer- based stalling avoidance mechanism as the enhancement to the current 3GPP specifications. In our proposal, the duration of the timer is set or updated through dynamic monitoring on the status of each HARQ process. We show with illustrative examples and simulations that the proposed mechanism reduces considerably extra packet delay incurred during reordering operations.

We consider a two-hop relaying network in which orthogonal frequency division multiplexing (OFDM) is employed for the source-to-destination, the source-to-relay and the relay- to-destination links. Amplify-and-forward (AF) and decode-and- forward (DF) policies are both discussed with or without two-hop diversity, respectively, for the relaying network with a sum-power constraint. An unified approach is used for optimal power allocation in the four different relaying scenarios. First, equivalent channel gains are developed for any given subcarrier pair in each scenario, and then optimal power allocation can be obtained by applying the classic water-filling method. Moreover, we provide the proof to the optimality of sorted subcarrier pairing for AF and DF relaying without diversity, which, combined with optimal power allocation, can offer further performance gain.

Installing multiple antennas at user equipments (UEs) may pose great challenges. In virtual multiple-input multiple-output (MIMO) concept, multiple single-antenna UEs can be grouped to transmit signals at the same time. Their signals can be separated at the base station (BS) by the same methods already used in conventional point-to-point MIMO scenarios. An important problem in virtual MIMO application is which users can be scheduled simultaneously to achieve a good balance between various system targets, e.g. aggregate throughput and user fairness. In this paper, a novel scheduling scheme is proposed which combines the advantages of proportional fair and maximum rate rules, based on successive interference cancellation (SIC) MIMO receiver architecture. Simulation results show that the proposed scheme can achieve a good tradeoff between system throughput and user fairness. Compared with other scheduling schemes already proposed in virtual MIMO context, e.g., orthogonality pairing scheduling (OPS), the proposed scheme can be justified by its low computational complexity and flexibility.

We consider a multi-hop wireless sensor network in which a large number of sensor nodes are grouped into cooperative clusters. Multi-hop transmission is carried out between the source and the destination nodes by concatenating consecutive cluster-to-cluster hops. For each hop, both the transmit and the receive clusters can exploit node cooperation such that cooperative distributed multiple-input multiple-output (MIMO) channels can be formed. As proposed in [1], a time-division protocol is employed for transmissions within a cluster and between clusters, i.e., the intra-cluster slot is used for broadcasting within the transmit cluster, and the inter-cluster slot is used for transmissions between clusters. Distinguished from the scheme in [1] that space-time codes (STC) are utilized for inter-cluster transmissions, random beamforming is proposed in this paper, which is shown to outperform STC in term of energy efficiency provided that the number of nodes within receive cluster is adequately large. We demonstrate that even with moderate number of nodes within receive cluster, e.g., 10 nodes, random beamforming can offer higher energy efficiency for inter-cluster links, at 5% outage rate. The "random" nature incorporated in random beamforming scheme assigns the clusterhead node within receive cluster in an alternate manner, thus balancing energy consumption within receive cluster.

Frequency allocation is a critical issue for cellular relaying networks. In this paper we present spectrum-efficient frequency allocation policies that are applicable for fixed two-hop cellular relaying networks. The frequency allocation problem is decomposed into two sub-problems: inter-cell and intra-cell frequency allocation. The goal is to make more users to be served with satisfactory service quality. Through numerical analysis, the basic inter-cell frequency allocation scheme is proposed, including frequency reuse pattern and reuse factors for each type of links. Then we propose a method to realize safe intra-cell frequency reuse, in the sense that higher spectrum efficiency is achieved through this tighter frequency reuse while the signal- to-interference (SIR) quality for the links of concern is still guaranteed. Simulations show that our schemes are beneficial to obtain more satisfied users and low outage ratio, when compared to the cases without intra-cell frequency reuse scheme and the cases with fixed intra-cell frequency reuse scheme.