Cooperative MIMO Transmission Research Articles

Multi-Hop Cooperative MIMO Transmission in Wireless Sensor Networks

This article presents a multihop spatial multiplexing cooperative MIMO (SM-CMIMO) transmission scheme. The SM-CMIMO scheme employs a novel configuration on MIMO system which works in a cooperative manner, to achieve a least energy consuming path, with reduced rate of bit error and higher data rate. In this approach, list of relay nodes located in equal distance at any route towards destination selected. The source selects a set of relay nodes and cooperative nodes to frame a cooperative MIMO System. The cooperative nodes are selected using NSA (Node Selection Algorithm) with no channel state, bit error rate and data rate constraints. Each hop is evaluated for suitable replacement with V-MIMO configurations. To reduce the depletion of energy at MIMO cooperative network, at the middle of these hops, relay nodes are selected and evaluated for possible replacement of long-hop with two smaller MIMO transmission hops. We show that proposed SM-CMIMO transmission offers significant energy efficiency improvement compared with SISO transmission. The performance of the system degrades indirectly with the channel correlation.

Dynamic UE clustering for distributed MIMO cooperative transmission

Dynamic UE clustering for distributed MIMO cooperative transmission

An energy‐efficient cooperative MIMO transmission with data compression in wireless sensor networks

In this letter, a novel metric for energy‐efficient cooperative transmission with data compression in wireless sensor networks (WSNs) is proposed. Under the guidance of the new metric, energy consumption is optimized by considering the correlation between data generated by the sensor nodes. The distance between sensor nodes inside the cluster affecting the data correlation as a key factor is analyzed, and the corresponding optimal value is used to reduce the energy consumption. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

A Novel Energy-efficient Cooperative Transmission Scheme Based on V-BLAST Processing and ICA clustering for WSNs Lifetime Maximization

In wireless sensor network, one of the main objectives is how to improve its lifetime because the sensor nodes are generally energy-limited. Thus, providing ways to optimize energy Consumption, which ultimately increases the network lifetime, is of great importance. In this paper, we propose and evaluate an energy-efficient cooperative MIMO transmission scheme based on V-BLAST technique. In proposed scheme the clustering is done based on Imperialist Competitive Algorithm (ICA) then V-BLAST technique based virtual MIMO transmission are used. This proposed protocol performance is analytically and experimentally is compared with previous presented works. From the analysis and the simulation results, it is seen that the proposed method can reduce the energy consumption of the network and prolong the sensor networks lifetime compared with existing techniques.

On the Performance of MIMO Cooperative Transmission for Broadband Vehicular Networks

In this paper, we investigate the performance of a cooperative vehicular network over a doubly selective fading channel using multiple antennas at source and destination vehicles. Under the assumption of amplify-and-forward (AF) relaying with orthogonal cooperation protocol and Alamouti-type space-time block coding (STBC), we derive a pairwise error probability (PEP) expression and demonstrate the achievable diversity gains. Our results demonstrate that, via proper linear constellation precoding and digital phase sweeping (DPS), the cooperative vehicular scheme is able to extract the maximum available diversity in frequency (through multipath diversity), time (through Doppler diversity), and spatial (through antenna and cooperative diversity) dimensions. We further conduct Monte Carlo simulations to confirm the analytical derivations and present the error rate performance of the vehicular scheme under various mobility conditions and scenarios.

An Optimized Cooperative Transmission based on V-BLAST Technique and GA clustering for Wireless Sensor Networks

Energy saving is an essential issue in the design of a wireless sensor network because the sensor nodes are generally energy-limited. Thus, minimizing and balancing the energy consumption for nodes are becoming important in terms of extending the network lifetime. In this paper, a novel energyefficient cooperative MIMO transmission mechanism based on V-BLAST technique is proposed. Compared with previous presented structures, in proposed scheme the clustering is done based on Genetic Algorithm then V-BLAST technique based cooperative MIMO transmission are used. An energy consumption is developed to investigate the energy saving performance. The performance of suggested protocol is compared with the LEACH and previous work. Simulation results demonstrate that proposed scheme can achieve better network lifetime and decrease the energy consumption of the network.

A Noise-Correlated Cancellation Transmission Scheme for Cooperative MIMO Ad Hoc Networks

A new transmission scheme based on noise-correlated cancellation (NCC) is proposed, which absorbs the advantages of phase-inversion symmetric method and cooperative MIMO technology and makes full use of the correlation of noise in the adjacent channels to reduce channel noise. This paper firstly presents the implementation process of NCC transmission scheme in detail. Further, through theoretical analysis, it is showed that the signal-to-noise ratio gain which the proposed NCC transmission scheme gets is at least 4 times greater than the signal-to-noise ratio gain which the traditional cooperative MIMO transmission scheme gets. Finally, simulation experiment results also verify that the proposed NCC transmission scheme can make the channel capacity per bandwidth of cooperative MIMO Ad Hoc networks improve significantly and bit error rate (BER) of the network reduce greatly, which will help to expand application scopes of cooperative MIMO Ad Hoc networks.

A Heterogeneous-aware Cooperative MIMO Transmission Scheme in WSN

A heterogeneous-aware cooperative MIMO transmission scheme (HAMS) is proposed to optimize the network lifetime and save energy for energy heterogeneous wireless sensor networks (WSN). This scheme extends the traditional low-energy adaptive clustering hierarchy (LEACH) protocol to enable the cooperative MIMO transmission between the sink and clusters. Through the adaptive selection of cooperative nodes and the cooperative MIMO transmission, HAMS can gain effective performance improvement in terms of taking advantage of the presence of node heterogeneity. Based on the energy consumption model developed in this paper, the optimal parameter to minimize the overall energy consumption is found. Simulation results exhibit that HAMS can effectively save energy and prolong the network time. Furthermore, HAMS displays more resilient in different degree of heterogeneous wireless sensor networks.

Multicast Performance With Hierarchical Cooperation

It has been shown in a previous version of this paper that hierarchical cooperation achieves a linear throughput scaling for unicast traffic, which is due to the advantage of long-range concurrent transmissions and the technique of distributed multiple-input-multiple-output (MIMO). In this paper, we investigate the scaling law for multicast traffic with hierarchical cooperation, where each of the n nodes communicates with k randomly chosen destination nodes. Specifically, we propose a new class of scheduling policies for multicast traffic. By utilizing the hierarchical cooperative MIMO transmission, our new policies can obtain an aggregate throughput of Ω(( [( n)/( k)])1-e) for any e >; 0. This achieves a gain of nearly √{[( n)/( k)]} compared to the noncooperative scheme in Li 's work (Proc. ACM MobiCom, 2007, pp. 266-277). Among all four cooperative strategies proposed in our paper, one is superior in terms of the three performance metrics: throughput, delay, and energy consumption. Two factors contribute to the optimal performance: multihop MIMO transmission and converge-based scheduling. Compared to the single-hop MIMO transmission strategy, the multihop strategy achieves a throughput gain of ( [( n)/( k)])[(h-1)/( h(2h-1))] and meanwhile reduces the energy consumption by k[( α-2)/ 2] times approximately, where h >; 1 is the number of the hierarchical layers, and α >; 2 is the path-loss exponent. Moreover, to schedule the traffic with the converge multicast instead of the pure multicast strategy, we can dramatically reduce the delay by a factor of about ( [( n)/( k)])[(h)/ 2]. Our optimal cooperative strategy achieves an approximate delay-throughput tradeoff D(n,k)/T(n,k)=Θ(k) when h→ ∞. This tradeoff ratio is identical to that of noncooperative scheme, while the throughput is greatly improved.

Energy-Efficiency of MIMO and Cooperative MIMO Techniques in Sensor Networks

We consider radio applications in sensor networks, where the nodes operate on batteries so that energy consumption must be minimized, while satisfying given throughput and delay requirements. In this context, we analyze the best modulation and transmission strategy to minimize the total energy consumption required to send a given number of bits. The total energy consumption includes both the transmission energy and the circuit energy consumption. We first consider multi-input-multi-output (MIMO) systems based on Alamouti diversity schemes, which have good spectral efficiency but also more circuitry that consumes energy. We then extend our energy-efficiency analysis of MIMO systems to individual single-antenna nodes that cooperate to form multiple-antenna transmitters or receivers. By transmitting and/or receiving information jointly, we show that tremendous energy saving is possible for transmission distances larger than a given threshold, even when we take into account the local energy cost necessary for joint information transmission and reception. We also show that over some distance ranges, cooperative MIMO transmission and reception can simultaneously achieve both energy savings and delay reduction.