This work addresses the challenge of simultaneous position and orientation (SPAO) estimation in visible light systems, a task complicated by interference from wall reflection components. To overcome this issue, a novel visible light SPAO system is proposed that integrates a single light-emitting diode (LED) and a single photodiode (PD) with an optical intelligent reflecting surface (IRS). Unlike traditional visible light SPAO methods, the proposed system determines the number of independent measurement links based on the number of positioning time slots rather than the number of LEDs, PDs, or IRSs. The system effectively mitigates the adverse effects of wall reflection components by relying solely on the channel gain between the IRS and the user device. The Cramer–Rao Lower Bound (CRLB) is derived as a performance benchmark for the SPAO system. Building on this benchmark, an enhanced differential evolution (DE) algorithm is introduced, balancing global exploration and local exploitation. The algorithm incorporates mechanisms to escape local optima, ensuring improved convergence to the global optimal solution. Simulation results demonstrate that the proposed visible light SPAO system’s performance closely approaches the CRLB and surpasses state-of-the-art baseline methods.

The reconfigurable intelligent surface (RIS) aided index modulation (IM) is a promising technology for next-generation wireless communications. However, acquiring channel state information (CSI) for RIS-based IM requires expensive pilot overhead, especially for the IM in multiple domains. In this paper, a novel rectangular differential reflecting spatial modulation (RDRSM) system is proposed for the RIS-aided multiple-input multiple-output (MIMO) system. Specifically, the proposed multi-antenna-activated RDRSM (M-RDRSM) scheme utilizes a rectangular dispersion matrix (DM) to jointly map a digital beamforming (DBF) weight vector and a RIS reflection pattern to perform the rectangular differential modulation. A thorough analysis presents that the proposed M-RDRSM scheme can achieve high-spectral efficiency, low complexity of the system, and noncoherent decoding without prior knowledge of CSI in the space-reflection dual-domain IM. Further, the proposed M-RDRSM scheme is simplified to a single-antenna-activated RDRSM (S-RDRSM) scheme, which can reduce the hardware cost and avoid the inter-antenna synchronization problem more effectively. Simulation results demonstrate that the proposed RDRSM scheme performs better in terms of bit error rate performance and achieve a lower decoding complexity than the existing correlated differential IM schemes with the same achievable spectral efficiency.

Abstract User scheduling algorithms in non‐orthogonal multiple access (NOMA) have attracted much attention to improve the performance of the communication system. Here, a low complexity user scheduling algorithm aimed for the maximum number of active users in the single NOMA cluster ensuring the individual minimum rate requirement is proposed. Based on the precondition of the maximisation of the number of active users, the maximum sum‐rate strategy is further integrated into the algorithm to compose a multi‐round user scheduling algorithm. Moreover, a computational‐complexity reduction algorithm is also introduced and has proved to be conveniently used in practical operation. Simulation results have shown that, compared with other existing user scheduling algorithms, the proposed user scheduling algorithms can achieve the maximum number of active users while ensuring their individual minimum rate requirements, and significantly improve the performance of the sum‐rate among the cases when the maximum number of active users is achieved. Furthermore, the proposed multi‐round and computational‐complexity reduction user scheduling algorithms have shown better performance than the exhaustive search in terms of the computational complexity.

In this paper, we propose enhanced Reed-Muller (RM) and Polar decoder for SDN-based C-RAN fronthaul. The simulation results show that our proposed algorithm outperforms traditional decoding algorithm in terms of average number of connected user equipment to RRHs, and the feasibility of decoding the RM codes by the Successive Cancellation (SC) decoding algorithm is verified by comparing the performance and decoding time of the RM and Polar codes under the SC and Belief Propagation (BP) iterative algorithm. The simulation results show that the decoding time of SC decoding algorithm is reduced about 98.98% compared with the BP decoding algorithm. For the BP decoding algorithm with excellent decoding performance but long decoding time, this paper proposes an improved BP decoding algorithm based on early terminating iteration criterion of the absolute values difference for the likelihood, which reduces the computational complexity of criterion. The simulation results illustrate that the early-terminating iteration criterion proposed in this paper reduces the computational complexity, thereby reducing the decoding delay and energy consumption effectively, and satisfying the low complexity and energy consumption decoding requirements.

Considering the scenarios where the localization accuracy of the agent is required to meet a desired requirement rather than achieve the best result, it is not necessary for all nodes to participate in positioning the agent. In this paper, a reference node (RN) selection algorithm for wireless network localization under desired accuracy is proposed. A robust error bound (REB) is derived as the RN selection metric and the concept of equal-REB contour is given, based upon which the searching region (SR) for selecting RNs is defined. In REB, the measurement errors of distances are taken into consideration and modeled as a Gaussian noise whose variance is proportional to the square of the distance. The proposed RN selection strategy selects nodes from the SR instead of the whole network region iteratively until the localization accuracy meets the desired requirement. Simulations show that the RN-selection algorithm can select the RN sets providing better localization accuracy when using REB metric. Moreover, the improved performance in terms of power conservation of the proposed algorithm is evaluated through simulation results.

To address the energy‐efficient (EE) routing problem in software‐defined wireless sensor networks (SDWSNs), in this study, a centralised routing algorithm, namely, the interference‐aware EE routing algorithm (IA‐EERA), is proposed to extend the network lifetime (NL) in SDWSNs. Both the link quality of service requirements and the balance between the link energy loads are considered in the proposed IA‐EERA when selecting the EE relays. Concretely, the IA‐EERA comprises the EE relay selection (RS) and the centralised relay scheduling schemes, which are responsible for generating a valid link set with RS priorities and scheduling the eligible relay nodes with expected link rates from the valid link set, respectively. For supporting the network compatibility and scalability, we propose a hierarchical SDWSN based network architecture, upon which the IA‐EERA can be devoted to solving the EE routing problem in the relay layer of SDWSN. Simulation results show that for one data source without interference, the proposed IA‐EERA can significantly improve the NL compared with the traditional routing algorithm utilising the energy efficiency maximisation. For multiple data sources incurring interference at nodes, the IA‐EERA is able to reduce the NL‐dropping rate by adjusting the interference‐aware parameter that affects the RS priorities

Efficient data delivery in vehicular named data networks (VNDNs) can immensely enhance the safety and entertainment for drivers. For this purpose, in-network caching is used to expedite data delivery. In this work, a distributed probability-based caching with content-location-awareness (DPC-CLA) is proposed for efficient data delivery in VNDNs, where the roadside-units (RSUs) with caching capabilities can accurately access the relatively popular contents of the received packets by normalizing the reciprocal sum of the request hops in an indefinite period. In addition, the RSUs can also perceive the surrounding cache locations using the weighted recursive sum of the neighbouring cache intervals. Simulation results show that the proposed DPC-CLA performs better than four existing caching mechanisms in terms of the average number of hops and the cache hit ratio.

In this paper, an energy-efficient relay selection (RS) algorithm is proposed for line-of-sight (LOS) transmissions in wireless sensor networks (WSNs) with blockage. To find the energy-efficient routing for given sensor and sink node pair, the best RS criteria are employed to approach the optimal relay position (ORP) of the effective relay search region (RSR) in multiple different ways. For example, the minimal distance criterion is used to generate the minimal RSR centered on ORP during the initial selection phase. Subsequently, we enlarge RSR and apply the minimal impact-probability criterion to reduce the impact of obstacles on energy efficiency for LOS transmissions. Lastly, the minimal projection criterion is used to refine the results of RS based on the minimal impact-probability criterion. Simulation results show that the proposed algorithm based on the best RS criteria with composite ways is able to reduce the energy consumption as well as the impact of obstacles when the RSR's radius increment is less than a certain threshold.

This paper presents an optimal roadside unit (RSU) placement method for vehicle localization in Vehicle Ad-hoc Networks (VANETs). Since the RSU layout can significantly affect the performance of localization algorithms, the proposed method needs to find an optimal K-coverage RSU placement, to ensure the best localization accuracy while using minimum number of RSUs. We adopt the Geometric Dilution of Precision (GDOP) metric to evaluate the accuracy provided by RSU placements, and derive the expression of GDOP towards received signal strength (RSS) and hybrid parameter estimators, respectively. There are two steps contained in the proposed method. Firstly, the optimal elementary pattern is obtained and applied to form the 1-coverage placement. Secondly, the optimal K-coverage placement based on K-layer elementary patterns is found by minimizing the average GDOP of the road area, using asynchronous particle swarm optimization (APSO) algorithm. In simulations the convergence and stability of APSO solutions are verified, then our method is compared with existing uniform placement method, the results show that the proposed method can achieve better positioning performance.

In this paper, we propose a weighted cooperative localization algorithm with the ability to mitigate non-line-of-sight (NLOS) propagations in wireless networks. The link condition indicator (LCI) for each connection is calculated based on the amplitude and delay statistics of channel responses. We partition the ambiguity of link condition into N levels according to the LCI values. With the distance-dependent LOS/NLOS probability suggested by the 3rd Generation Partnership Project (3GPP), the relationship between LOS/NLOS probability and the time-of-arrival (TOA) of inter-node signal transmission is derived. We incorporate this probability into N-level LCI range regions and propose the N probabilistic hard weight (N-PHW) strategy for the cooperative localization, which penalizes the NLOS-induced positive biases by weighting the belief terms introduced by the conventional cooperative localization algorithm, the sum-product algorithm over a wireless network (SPAWN). Simulation results show that the proposed weighted algorithm significantly improves the localization performance in terms of localization accuracy, especially in serious NLOS environments.

Regular zero-forcing (RZF) precoding algorithm is well- known as its low complexity and high performance in massive MIMO systems. However, when the number of transmitting antennas increases, the matrix inversion in RZF leads to high algorithmic complexity. In this paper, we propose an improved Newton iteration to estimate the matrix inversion in RZF precoding. Compared with the traditional Newton iteration, the performance improvement of the proposed algorithm is achieved in both of the fast algorithm convergence and the average user arrival rate in RZF precoding.

In this study, the authors propose an improved localisation algorithm in the software‐defined sensor networks (SDSNs). This algorithm includes a node‐selection strategy under the whole network power constraint, based on the software‐defined networking (SDN) technique for providing the centralised control of the network. The analogous Cramer‐Rao lower bound (A‐CRLB) value is derived for each participating node, which represents a fundamental bound on the variance of the position estimator and is used to evaluate the contribution of each node to localisation accuracy. On the basis of A‐CRLB values, the most helpful nodes for localisation are selected to maximise the sum of the nodes' contributory values to the localisation accuracy. With the global network knowledge provided by the SDN controller in the SDSN, the node‐selection strategy is formulated into a 0‐1 programming problem on the premise of power satisfaction of each node. Furthermore, the proposed node‐selection ‐based localisation algorithm is applied to both noncooperative and cooperative localisation scenarios. Simulation results show that the proposed algorithms provide efficient and effective localisation schemes in SDSNs, and can improve the performance in terms of both the selection convergence speed and the localisation accuracy.

In this study, the hybrid‐access problem in multi‐femtocell networks, where multiple femtocell registered users (FRUs) and unregistered users (FURUs) coexist, is solved based on the optimal resource allocation using Stackelberg game. The main idea of the authors’ proposed scheme is to have the femtocell base station (FBS) allocating resources to FRUs freely to guarantee their quality of service (QoS), and then obtaining the compensation for offering the hybrid‐access through selling the remaining resources to FURUs with high motivation. Based on the Stackelberg game involving the non‐cooperative competition among the FBS and multiple FURUs, a dynamic hybrid‐access control scheme is proposed and analysed for single‐femtocell access. Then a dynamic multi‐round hybrid‐access scheme (DMRHAS) with post‐DMRHAS is further designed for multi‐femtocell hybrid‐access. Simulation results show that the proposed schemes have the FBS not only protect FRUs' QoS, but also dynamically determine the list of accessible FURUs according to the channel power gains of FURUs and the change of FRUs' QoS demands, through pricing the FURUs.

In this study, we propose a novel dynamic hybrid access algorithm for single femtocell network with two different types of users, the femtocell registered users (FRUs) and unregistered users (FURUs). Considering the selfish nature of the femtocell, how to provide enough incentives to the femtocell base station (FBS) for sharing its resources with the FURUs is challenging. Different from the previous works in this area, we adopt the Stackelberg-game modeling to represent the competition behaviors of the FBS and the users. Specifically, the proposed framework has the FBS to allocate resources to the FURUs through pricing while maintaining the quality of service (QoS) of the FRUs, which is done via the optimal solutions of the maximization of the utility functions of the buyers and the revenue of the seller. Simulation results show that upon the QoS of the FRUs are protected, the FBS dynamically determines the list of the accessible FURUs according to the assigned gain to the FURUs and the change of the FRUs' QoS demands.

Femtocell with the open access mode benefits the macrocell users (MUE) which locate closely to the femtocell base station (FBS). However, how to enhance these users' performance with the femtocell registered users quality of service (QoS) protection becomes a major problem. Deploying relay outside the femtocell networks is an economical and effective option to reduce the cross-tier interference while improving the network capacity and indoor coverage in the cellular networks. In this paper, an optimal power allocation scheme considering the protection of the femtocell registered users is proposed in the open access femtocell network assisted with a relay node, which operates under a novel amplify-and-forward (AF) relaying protocol, for the downlink. The power allocation problem is formulated with the objective of maximizing the sum-transmission-rate of the neighboring macrocell users (NMUEs) which perform the handovers from the macrocell to the femtocell due to the degraded channel QoS of the macrocell. This optimization is subject to the constraints of the required transmission rates of the femtocell registered users (FUEs), the thresholds of the cross-tier interferences to the users kept in the macrocell, and the total transmit powers of the FBS and the relay node, etc. We solve the optimization problem via the dual decomposition method. Simulation results have shown that our proposed scheme can protect the QoS required by the FUEs. It also illustrates the better performance of the proposed optimization methodology in terms of the sum-transmission-rate of the NMUEs than the traditional femtocell method which has no presence of the relay node.

This study proposes an analytical model and an effective scheme for the periodic broadcast on the control channel in vehicular ad hoc networks (VANETs). An improved Markov model for analysing the performance of the periodic broadcast in VANETs is established. Compared with the traditional two‐dimensional Markov chain models, the improvement of our proposed model is achieved by the considerations of the unsaturated traffic conditions with the deterministic message generation at each node, modelled by a discrete‐time D/M/1 queue and the control mechanism of freezing the backoff‐time counter. In adapting to the change of the vehicle densities, the authors propose to use the dynamic contention window (DCW), instead of the fixed contention window (CW), for the broadcast in the IEEE 802.11p medium access control in VANETs. For a certain vehicle density, a best CW size is chosen to achieve a more effective broadcast. Simulation results show that the proposed DCW‐based broadcast performs better than the traditional fixed‐CW‐size broadcast in terms of the packet collision probability. The results also validate our proposed Markov model and its performance improvement than the scheme without the consideration of freezing the backoff‐time counter.

In this paper, we study optimal transmission scheduling and congestion control in multi-hop device-to-device (D2D) communications underlaying cellular networks. The optimization is not only based on the cellular and D2D link qualities but it also takes the interference situation for each possible mode and the quality of service (QoS) requirements of each user into account. The problem is formulated as an overall time-averaged system throughput maximization with system stability provision. By manipulating the formulation and using the Lyapunov optimization theory, the original problem can be decomposed into an end-to-end rate control problem and a joint routing, channel assignment, and power allocation problem. We provide a lower bound of the system throughput and thus the proposed algorithm can achieve an approximate maximization. Simulation results show that the algorithm simultaneously improves the system throughput and stability compared to the scenario where communication modes are fixed for all sources.

The Internet is growing rapidly, causing concerns that the address space for IPv4 may soon be used up. Taking a snapshot of the Internet size can help in planning the future evolution and capabilities of the Internet as well as planning the implementation of the next generation IPv6. We extended our previous work on measuring the number of publicly accessible web servers to make more accurate measurements of the size of the Internet. An improved importance sampling approach is introduced which achieves a significant gain over Monte Carlo methods. The growth of the Internet is mapped by periodic measurements of the number of active web servers.

Measuring the size of the Internet via Monte Carlo sampling requires probing a large portion of the Internet protocol (IP) address space to obtain an accurate estimate. However, the distribution of information servers on the Internet is highly nonuniform over the IP address space. This allows us to design probing strategies based on importance sampling for measuring the prevalence of an information service on the Internet that are significantly more effective than strategies relying on Monte Carlo sampling. We present thorough analysis of our strategies together with accurate estimates for the current size of the Internet Protocol Version 4 (IPv4) Internet as measured by the number of publicly accessible web servers and FTP servers.