Cooperative Multiple-input Multiple-output Research Articles

Latency and Residual Energy Analysis of MIMO Heterogeneous Wireless Sensor Networks

Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized application of MIMO technology within WSNs. This approach operates effectively, especially in challenging and resource-constrained environments. By facilitating collaboration among sensor nodes, Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments. Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring, industrial automation, and healthcare applications. This research paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO using Network Simulator NS2.35 for analysis of End to End Delay for packet transmission and Residual energy of nodes. The research work shows application of MIMO in Wireless Sensor Networks with considerable improvements in Quality of Service parameters which is achieved through Spatial Multiplexing and Diversity Gain. MIMO enables multiple spatial streams, allowing several data streams to be transmitted simultaneously on the same channel. This increases the overall throughput as multiple sensors can transmit their data concurrently without interference. MIMO systems also provide diversity gain by transmitting multiple copies of the same data over different antennas which helps in mitigating the effects of fading and interference, resulting in a more reliable and higher-throughput communication link as compared to a SISO channel. Another advantage of employing MIMO in WSN is reduction in End-to-End delays in data transmission. Last but not the least, MIMO can be configured to optimize the power consumption of individual sensors by adjusting the number of antennas used and transmission power levels based on channel conditions. Hence, MIMO can help to extend the network's lifetime by conserving energy in resource-constrained sensor nodes by preservation of Residual Energy.

Deep Learning Based Cooperative MIMO Systems for Wireless Body Area Networks

Wireless Body Area Network (WBAN) is widely applied in various fields, including healthcare, sports, wellness, and assistive technologies, by offering the benefits of convenience, reliability, low latency, privacy, and customization. However, the propagation characteristics of the WBAN channel can impact the reliability of transmission, which is particularly crucial in healthcare systems. To address this issue, this article presents a novel approach using deep learning-based cooperative Multiple-Input Multiple-Output (MIMO) systems that leverage the autoencoder (AE) technique. In our proposed approach, we utilize the AE-based cooperative MIMO systems with two different techniques: Amplify-and-Forward (AE-AF) and Decode-and-Forward (AE-DF). The AE-AF scheme operates without needing training parameters at the relay node, whereas the AE-DF scheme necessitates training parameters at the relay node. Both schemes aim to overcome challenges such as multipath propagation phenomena, thereby enhancing the performance of on-body communication systems. Additionally, we introduce two combinators, Minimum Mean Square Error (MMSE) scheme and Radio Transformation Network (RTN), to effectively mitigate co-channel interference (CCI) in the received signal streams and improve the bit error rate performance of the AE-AF and AE-DF systems. We assess the performance of these systems in scenarios with and without direct links. Simulation results demonstrate significant performance improvements compared to baseline cooperative MIMO systems using MMSE combining, namely AF-MMSE and DF-MMSE systems. Notably, the proposed systems employing RTN combination, including both direct and relay paths, achieve a 7.5 dB gain over the baseline when all nodes are equipped with two transceiver antennas.

Joint Transmission Null Beamforming for MIMO Full-Duplex Wireless Communication System

Cancellation of self interference (SI) is an important technology in order for wireless communication system devices to perform full-duplex communication. In this paper, we propose a novel self-interference cancellation using null beamforming to be applied entire IEEE 802.11 frame including the legacy part for full-duplex wireless communication on Cooperative MIMO (Multiple Input Multiple Output). We evaluate the SI cancellation amount by the proposed method using a field programmable gate array (FPGA) and software defined radio (SDR), and show the experimental results. In the experiment, it is confirmed that the amount of SI cancellation by the proposed method was at least 18dB. The SI cancellation amount can be further potentiated with more accurate CSI (channel state information) by increasing the transmission power. It is shown that SI can be suppressed whole frame which includes legacy preamble part. The proposed method can be applied to next generation wireless communication standards as well.

Configurable virtual MIMO via UAV swarm: Channel modeling and spatial correlation analysis

Air-to-ground wireless channel modeling for unmanned aerial vehicle (UAV) communications has been widely studied. However, channel modeling for UAV swarm-enabled cooperative communication still needs investigation, where the impact of UAV positions on the spatial channel characteristics is of particular importance. In this paper, we consider a UAV swarm-enabled virtual multiple input multiple output (MIMO) system, where multiple single-antenna UAVs cooperatively transmit to multiple ground users (GUs). We establish a common coordinate system, as well as a UAV swarm-oriented coordinate system, to describe the relative positions of the GUs and the UAV elements, respectively. Based on the established coordinate systems, geometric ray superposition method is applied to describe the spatial channel matrix. The proposed modeling framework can be directly used to describe the line-of-sight and two-ray propagations, and can be extended for including more practical spatial features such as multipath scattering, inter-UAV blockage, and random UAV jittering, etc. Based on the proposed model, we further analyze the spatial correlation among the virtual MIMO links of GUs located at different positions. Via extensive simulations, we show that thanks to the flexible deployment of UAVs, the virtual MIMO array structure can be conveniently configured to get desired channel properties, such as the channel capacity, eigenvalue and condition number distribution, and spatial correlation distribution. This shows the possibility and importance of exploiting a new design dimension, i.e., the UAV swarm pattern, in such cooperative virtual MIMO systems.

Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks

The energy problem has become one of the critical factors limiting the development of underwater wireless sensor networks (UWSNs), and cooperative multiple-input–multiple-output (MIMO) technology has shown advantages in energy saving. However, the design of energy-efficient cooperative MIMO techniques does not consider the actual underwater environment, such as the distribution of nodes. Underwater magnetic induction (MI)-assisted acoustic cooperative MIMO WSNs as a promising scheme in throughput, signal-to-noise ratio (SNR), and connectivity have been demonstrated. In this paper, the potential of the networks to reduce energy consumption is further explored through the joint use of cooperative MIMO and data aggregation, and a cooperative MIMO formation scheme is presented to make the network more energy efficient. For this purpose, we first derive a mathematical model to analyze the energy consumption during data transmission, considering the correlation between data generated by nodes. Based on this model, we proposed a cooperative MIMO size optimization algorithm, which considers the expected transmission distance and transmission power constraints. Moreover, a competitive cooperative MIMO formation algorithm that jointly designs master node (MN) selection and cooperative MIMO size can improve energy efficiency and guarantee the connectivity of underwater nodes and surface base station (BS). Our simulation results confirm that the proposed scheme achieves significant energy savings and prolongs the network lifetime considerably.

A comprehensive review of cooperative MIMO WSN: its challenges and the emerging technologies

The distributed nodes of a Wireless Sensor Network (WSN) cooperate among themselves to emulate a virtual multi-antenna system to get similar benefits as the conventional MIMO systems. In WSN, such a system is known as the Cooperative Multiple Input Multiple Output (CMIMO) system. A CMIMO system has an enormous capacity to improve the performance of a WSN. But the increasing demand in the data rate and the desired Quality of Services (QoS), necessitates a revival in the way CMIMO was originally perceived in the early 1990s. Therefore, this article identifies several emerging supportive technologies such as the Compressive Sensing (CS), Simultaneous Wireless Information and Power Transfer (SWIPT), over the air computation, etc. which can be integrated to the CMIMO framework for enhancing the network performance in terms of throughput, delay, Energy Efficiency (EE), etc. The inclusion of these novel ideas necessitates further exploration of CMIMO in WSN along with its associated challenges and their possible solutions. This article provides a comprehensive overview of a CMIMO WSN along with its challenges which have been classified based on the layers of the protocol stack. Since energy efficiency is a key concern in a WSN having scarce energy resources, the energy-saving techniques have been discussed in detail. Further, challenges and open issues have also been highlighted which opens up new research direction in the area.

Energy efficient decision fusion for differential space-time block codes in wireless sensor networks

The non-coherent techniques that do not require the channel state information have gained significant interest especially when multiple transmitter and receiver nodes are involved in communication. In this paper, we analyze the energy efficiency of differential and coherent cooperative Multiple-input Multiple-output (MIMO) method using space-time block codes (STBC). We exploit the benefits of the extension of the observation interval of differential STBC to three blocks in Wireless sensor networks (WSNs). We propose an energy efficient decision fusion (EEDF) algorithm in WSNs which utilizes the benefits of Multiple symbol differential detection (MSDD) decision fusion by optimally selecting the ring amplitude of the differential amplitude phase shift keying (DAPSK) constellation. The simulation results show that processing differential multiple symbols provides significant energy saving compared to the conventional two-symbol processing. Furthermore, significant performance gain is achieved for the proposed algorithm compared to 16 DPSK MSDD decision fusions.

Switched Max-Link Relay Selection Based on Maximum Minimum Distance for Cooperative MIMO Systems

In this work, we present a switched relaying framework for multiple-input multiple-output (MIMO) relay systems where a source node may transmit directly to a destination node or aided by relays. We also investigate relay selection techniques for the proposed switched relaying framework, whose relays are equipped with buffers. In particular, we develop a novel relay selection protocol based on switching and the selection of the best link, denoted as Switched Max-Link. We then propose the Maximum Minimum Distance (MMD) relay selection criterion for MIMO systems, which is based on the optimal Maximum Likelihood (ML) principle and can provide significant performance gains over other criteria, along with algorithms that are incorporated into the proposed Switched Max-Link protocol. An analysis of the proposed Switched Max-Link protocol and the MMD relay selection criterion in terms of computational cost, pairwise error probability, sum-rate and average delay is carried out. Simulations show that Switched Max-Link using the MMD criterion outperforms previous works in terms of sum-rate, pairwise error probability, average delay and bit error rate.

Design of Cooperative MIMO Wireless Sensor Networks With Partial Channel State Information

Wireless sensor networks (WSNs) play a key role in automation and consumer electronics applications. This paper deals with joint design of the source precoder, relaying matrices, and destination equalizer in a multiple-relay amplify-and-forward (AF) cooperative multiple-input multiple-output (MIMO) WSN, when partial channel-state information (CSI) is available in the network. In particular, the considered approach assumes knowledge of instantaneous CSI of the first-hop channels and statistical CSI of the second-hop channels. In such a scenario, compared to the case when instantaneous CSI of both the first- and second-hop channels is exploited, existing network designs exhibit a significant performance degradation. Relying on a relaxed minimum-mean-square-error (MMSE) criterion, we show that strategies based on potential activation of all antennas belonging to all relays lead to mathematically intractable optimization problems. Therefore, we develop a new joint relay-and-antenna selection procedure, which determines the best subset of the available antennas possibly belonging to different relays. Monte Carlo simulations show that, compared to conventional relay selection strategies, the proposed design offers a significant performance gain, outperforming also other recently proposed relay/antenna selection schemes.

Optimal Best Path Selection Algorithm for Cluster-Based Multi-Hop MIMO Cooperative Transmission for Vehicular Communications

Multiple-input multiple-output (MIMO) cooperation in cluster-to-cluster communication has shown improved network quality of services by utilizing less transmission power over the fading environment. This is an enhancement from the traditional cluster-based single-input single-output multi-hop relaying used in vehicular communications. In this paper, we deploy multi-hop MIMO clustering relay into vehicular communication for a two-lane road transportation scenario. We deploy precoder and receiver filter in each MIMO link that is characterized by a narrowband classical three-dimensional time-varying channel. With the aid of the precoder and minimum mean square error receiver filtering algorithm in MIMO communication, we derive the end-to-end network signal-to-noise ratio to find the optimal best path using max-min theory with equal power allocation in precoder matrices that minimizes the network mean square error. A low-cost close-optimal best path selection method is also proposed through mathematical modeling. Computer simulation results demonstrate the validity of the theoretical investigations in this work.

Relay Selection in Network-Coded Cooperative MIMO Systems

Network-coded cooperation (NCC) has recently gained interest as it improves the network throughput in multi-source cooperative systems. NCC has been studied for single-antenna terminals only. Employing multiple-input multiple-output (MIMO) techniques can significantly improve the performance of NCC systems. Furthermore, the existing relay selection (RS) strategies for NCC utilize the “max-min” end-to-end (E2E) criterion. This selection strategy (called Strategy $\mathcal {A}$ ) is complicated even for a network with single-antenna terminals as it requires global channel state information (CSI). This requirement makes it hard to implement RS-based NCC. To counter this issue, we introduce a new RS strategy (Strategy $\mathcal {B}$ ), which utilizes only the local CSI (not global CSI), significantly reducing the signaling overhead without sacrificing the performance. The performance of MIMO-NCC under Strategies $\mathcal {A}$ and $\mathcal {B}$ is studied over independent and non-identically distributed (i.n.i.d.) Rayleigh fading channels. Relays and the destination are equipped with multiple antennas, whereas sources have a single antenna. The exact outage probability expressions of the system under consideration are derived. The asymptotic outage expressions are further provided to obtain valuable insights into the practical system-design parameters such as the diversity order and coding gain. Furthermore, numerical results are provided in support of the analytical results.

Design and performance analysis of multiple-relay cooperative MIMO networks

In this paper, we propose a closed-form (i.e., without the need of any iterative procedure) joint optimization framework of the source precoder, the amplify-and-forward relaying matrices, and the destination equalizer for a cooperative multiple-input multiple-output (MIMO) wireless network. We study in depth such a design and carry out its performance analysis in terms of average symbol error probability (ASEP), which allows one to calculate the diversity order of the cooperative system. The ASEP is also evaluated via Monte Carlo simulations and compared with recent competitive alternatives. Results show that the proposed design performs better than or comparably to recently proposed iterative approaches, with lower computational requirements.

A Decentralized Reciprocity Calibration Approach for Cooperative MIMO

As a key technology to improve the coverage and throughput of distributed wireless network, cooperative multiple-input multiple-output (CO-MIMO) system jointly manipulates the precoders of multiple distributed base stations (BSs) to serve multiple mobile stations, simultaneously. However, in time division duplexing mode, independent ambiguity multiplicative factors induced by practical transceiver radio frequency circuits will break the reciprocity between the uplink–downlink channels, resulting in the failure of cooperative precoding in multiple BSs. In this paper, we develop an efficient decentralized reciprocity calibration approach with low overhead and complexity for CO-MIMO systems. Specifically, the calibration problem of CO-MIMO is first modeled as a least square (LS) problem. Based on the decomposition theory, the LS problem is decomposed into a master problem and several subproblems. In order to avoid gathering channel state information from distributed BSs, the master problem is solved jointly and iteratively at the BSs’ side, while the subproblems are solved independently at each BS. According to the decomposition results and the solving strategy, the calibration process is described as a decentralized algorithm. The simulation results demonstrate that better performance could be achieved compared with the centralized approach.

Performance Gains From Cooperative MIMO Radar and MIMO Communication Systems

In this letter, the coexistence of a multiple-input multiple-output (MIMO) radar and a distributed MIMO communication systems is studied. Target returns contributed from both the radar transmitters and communication transmitters are employed to complete the radar task, leading to a hybrid active-passive MIMO radar network. For the communication task, not only are the communication signals received directly from communication transmitters, but also those bounced off from the target are exploited to extract useful information. The target localization Cramer–Rao bound and mutual information are derived for the radar and communication systems, respectively. It is shown that there is a performance gain due to the cooperation between the radar and communication systems.

Delay-tolerant distributed space-time coding with feedback for cooperative MIMO relaying systems

An adaptive delay-tolerant distributed space-time coding (DSTC) scheme equipped with a feedback channel is proposed for two-hop cooperative multiple-input multiple-output (MIMO) networks. A maximum likelihood receiver and adjustable code matrices subject to a power constraint with a decode-and-forward cooperation strategy are considered with different DSTC antenna configurations. In the proposed delay-tolerant DSTC schemes, an adjustable code matrix is employed to transform the space-time coded matrices at the relay nodes. Stochastic gradient and least squares algorithms are also developed with reduced computational complexity. The proposed algorithms are then extended to a cooperative MIMO system using amplify-and-forward strategy and opportunistic relaying algorithms in order to develop a delay-tolerant coding scheme combined with optimal relay selection strategies. An upper bound on the pairwise error probability and a rank criterion analysis are derived which indicate the advantage of the proposed algorithms. Simulation results show that the proposed algorithms obtain significant performance gains and address the delay issue in cooperative MIMO systems as compared to existing DSTC schemes.

Generalized Beamforming Design for Cooperative MIMO Multirelay Networks with Infinite Constraints and Imperfect CSI

A generalized base station-relay-user equipment (BS-Relay-UE) beamforming design is investigated for a cooperative multiple-input multiple-output (MIMO) multirelay networks with imperfect channel state information (CSI). In order to minimize the worst-case mean square error (MSE) which is subject to a semi-infinite (SI) relay power constraints, a generalized optimal beamforming structure for the relay amplifying matrix is effectively proposed, and then the SI relay power constraints are converted into linear matrix inequalities (LMIs) version. In such conversion, the objective problem recasts as a decoupled biconvex semidefinite programming (SDP) one which can be efficiently solved by the proposed alternating algorithm. The system performance has been verified in terms of worst-case MSE using a set of qualitative analyses. The results show us that the proposed beamforming method outperforms the conventional schemes and can also effectively reduce the computational complexity when it is compared to the cutting-set schemes and also to the nonrobust ones.

Source Transmit Antenna Selection for Space Shift Keying With Cooperative Relays

In this letter, we propose a cooperative multiple-input multiple-output (MIMO) scheme combining transmit antenna selection (TAS) and space shift keying (SSK). In this scheme, source transmit antennas are selected and SSK is applied by using the selected antennas. Besides the direct link transmission, the relays, that decode the source signal correctly, take part in the transmission. Exact expressions and a considerably accurate approximate expression for the symbol error rate of the proposed SSK system are derived. It is shown that the proposed scheme outperforms the SSK system without TAS and also the conventional cooperative MIMO system, which employs source TAS, at practical signal-to-noise ratio values for especially high data rates and sufficient number of receive antennas at the destination.

Energy-harvesting-based RA-coded cooperative MIMO: Codes design and performance analysis

To overcome the power limitation and prolong the lifetime of the coded cooperation system, this paper proposes an energy-harvesting-based repeat-accumulate (RA)-coded cooperative multiple-input multiple-output (MIMO), where the relay is equipped with multiple antennas for information decoding and energy harvesting. Firstly, a kind of structured low-density parity-check (LDPC) codes – RA codes are introduced, and the RA codes for the source and relay are designed jointly to cancel all girth-4 cycles. Secondly, the optimal antenna selection algorithm is adopted by the relay to transmit the information. Furthermore, the outage probability and bit error rate (BER) of the system are analyzed. Theoretical analysis and numerical simulations show that the investigated system outperforms the corresponding point-to-point system under the same condition. Simulation result also demonstrates that BER performance of the system employing jointly designed RA codes is much better than that of general RA codes.

Evaluating Node Reliability in Cooperative MIMO Networks

Cooperative multiple input multiple output (Co-MIMO) strategies represent one approach to meet the growing requirements (i.e., higher throughput, enhanced coverage, low latencies, and reduced cost) of wireless communication services. In Co-MIMO networks, low-power relay nodes (RNs) are recruited by mobile users to cooperate as virtual antenna arrays. Although Co-MIMO architectures can offer significant improvement in both the performance and security of wireless networks, they are susceptible to attacks. In this paper, we propose a novel node reliability evaluation scheme to enhance the security of Co-MIMO networks. Leveraging the probe signal transmissions involved in physical-layer secret key generation schemes, two distributed node level reliability detection methods (one-shot and dynamic) are proposed to detect RNs that are noncooperative. Based on the fusion of information from the RNs, an overall reliability evaluation can be accomplished at a central server. Mobile users interested in collaboration can access this central server to determine which nodes to recruit for cooperation. Both the theoretical analysis and the simulation results are presented to illustrate the proposed node reliability evaluation schemes.

Large-Scale Multi-Cluster MIMO Approach for Cognitive Radio Sensor Networks

This paper proposes a large-scale cooperative multiple-input multiple-output (CMIMO) beamforming scheme for uplink (UL) access in broadband cognitive radio wireless sensor networks (CR-WSNs) sharing the same spectrum with a primary network and employing orthogonal frequency-division multiplexing. The CR-WSN is divided into clusters each consisting of cooperative nodes that form a virtual antenna array. Using particle swarm optimization (PSO), each cluster seeks the optimal transmit weight vectors that maximize the UL channel capacity of each cluster, while controlling the interference levels to the primary network. Under the assumption of very large number of sensor nodes at each cluster, semi-analytic expressions for the symbol error rate and the ergodic channel capacity of the CMIMO-based CR-WSN are derived and validated with Monte-Carlo simulation. The PSO-based capacity-aware (PSO-CA) scheme is compared with the one based on the traditional gradient search scheme (GS-CA) and the results show that PSO-CA requires considerably less computational complexity while achieving essentially the same level of performance as the GS-CA.