Energy-Efficient Data Collection over Underwater MI-Assisted Acoustic Cooperative MIMO WSNs

Underwater magnetic induction(MI)-assisted acoustic cooperative multiple-input-multipleoutput(MIMO) has been recently proposed as a promising technique for underwater wireless sensor networks(UWSNs).For the more,the energy utilization of energy-constrained sensor nodes is one of the key issues in UWSNs,and it relates to the network lifetime.In this paper,we present an energy-efficient data collection for underwater MI-assisted acoustic cooperative MIMO wireless sensor networks(WSNs),including the formation of cooperative MIMO and relay link establishment.Firstly,the cooperative MIMO is formed by considering its expected transmission range and the energy balance of nodes with it.Particularly,from the perspective of the node’s energy consumption,the expected cooperative MIMO size and the selection of master node(MN) are proposed.Sequentially,to improve the coverage of the networks and prolong the network lifetime,relay links are established by relay selection algorithm that using matching theory.Finally,the simulation results show that the proposed data collection improves its efficiency,reduces the energy consumption of the master node,improves the networks’ coverage,and extends the network lifetime.

Joint Iterative Decoding for Network-Coding-Based Multisource LDPC-Coded Cooperative MIMO

A network-coding-based multisource LDPC-coded cooperative MIMO scheme is proposed,where multiple sources transmit their messages to the destination with the assistance from a single relay.The relay cooperates with multiple sources simultaneously via network-coding.It avoids the issues of imperfect frequency/timing synchronization and large transmission delay which may be introduced by frequency-division multiple access(FDMA)/code-division multiple access(CDMA)and time-division multiple access(TDMA)manners.The proposed joint″Min-Sum″iterative decoding is effectively carried out in the destination.Such a decoding algorithm agrees with the introduced equivalent joint Tanner graph which can be used to fully characterize LDPC codes employed by the sources and relay.Theoretical analysis and numerical simulation show that the proposed scheme with joint iterative decoding can achieve significant cooperation diversity gain.Furthermore,for the relay,compared with the cascade scheme,the proposed scheme has much lower complexity of LDPC-encoding and is easier to be implemented in the hardware with similar bit error rate(BER)performance.

Performance analysis on channel capacity in cooperative MIMO system

Recent years,cooperative technology has taken a lot of attention since it can improve the bit error rate(BER) and lower the transmit power in radio mobile networks,especially when the direct channel between the source and the destination is poor.Cooperative multiple input multiple output(Co-MIMO) is a kind of MIMO technique,where the multiple inputs and outputs are formed via cooperation.The capacity of Co-MIMO system over wireless channel has been investigated a lot,however few papers pay attention to the locations of the channel that may affect the probability distributions of the variable and the effect of antenna spatial correlation.The results can be achieved by choosing sub-channels that is not related to other sub-channels.This paper focuses on this problem.The simulation results show that once we search the partner we should consider trade offs cooperation get optimum system performance.It further investigates that cooperation between different terminals can reduce antenna spatial correlation,thereby increase the capacity and throughput of the system,and even reach the ideal capacity of MIMO system.

OPTIMAL POWER ALLOCATION WITH AF AND SDF STRATEGIES IN DUAL-HOP COOPERATIVE MIMO NETWORKS

Dual-hop cooperative Multiple-Input Multiple-Output (MIMO) network with multi-relay cooperative communication is introduced. Power allocation problem with Amplify-and-Forward (AF) and Selective Decode-and-Forward (SDF) strategies in multi-node scenario are formulated and solved respectively. Optimal power allocation schemes that maximize system capacity with AF strategy are presented. In addition, optimal power allocation methods that minimize asymptotic Symbol Error Rate (SER) with SDF cooperative protocol in multi-node scenario are also proposed. Furthermore, performance comparisons are provided in terms of system capacity and approximate SER. Numerical and simulation results confirm our theoretical analysis. It is revealed that, maximum system capacity could be obtained when powers are allocated optimally with AF protocol, while minimization of system's SER could also be achieved with optimum power allocation in SDF strategy. In multi-node scenario, those optimal power allocation algorithms are superior to conventional equal power allocation schemes.

Power allocation in cooperative MIMO systems under individual power constraints

allocation （PA） plays an important role in capacity improvement for cooperative multiple-input multipleoutput （Co-MIMO） systems. Many contributions consider a total power constraint （TPC） on the sum of transmit power from all nodes in addressing PA problem. However, in practical implementations, each transmit node is equipped with its own power amplifier and is limited by individual power constraint （IPC）. Hence these PA methods under TPC are not realizable in practical systems. Meanwhile, the PA problem under IPC is essential, but it has not been studied. This paper extends the traditional non-cooperative water-filling PA algorithm to IPC-based Co-MIMO systems. Moreover, the PA matrix is derived based on the compound channel matrix from all the cooperative nodes to the user. Therefore, the cooperative gain of the IPC-based Co-MIMO systems is fully exploited, and further the maximal instantaneous capacity is achieved. Numerical simulations validate that, under the same IPC conditions, the proposed PA scheme considerably outperforms the non-cooperative water-filling PA and uniform PA design in terms of ergodic capacity.

Systematic energy-balanced cooperative transmission scheme in wireless sensor networks

Energy efficiency is a critical issue in wireless sensor networks （WSNs）. In order to minimize energy consumption and balance energy dissipation throughout the whole network, a systematic energy-balanced cooperative transmission scheme in WSNs is proposed in this paper. This scheme studies energy efficiency in systematic view. For three main steps, namely nodes clustering, data aggregation and cooperative transmission, corresponding measures are put forward to save energy. These measures are well designed and tightly coupled to achieve optimal performance. A half-controlled dynamic clustering method is proposed to avoid concentrated distribution of cluster heads caused by selecting cluster heads randomly and to get high spatial correlation between cluster nodes. Based on clusters built, data aggregation, with the adoption of dynamic data compression, is performed by cluster heads to get better use of data correlation. Cooperative multiple input multiple output （CMIMO） with an energy-balanced cooperative cluster heads selection method is proposed to transmit data to sink node. System model of this scheme is also given in this paper. And simulation results show that, compared with other traditional schemes, the proposed scheme can efficiently distribute the energy dissipation evenly throughout the network and achieve higher energy efficiency, which leads to longer network lifetime span. By adopting orthogonal space time block code （STBC）, the optimal number of the cooperative transmission nodes varying with the percentage of cluster heads is also concluded, which can help to improve energy efficiency by choosing the optimal number of cooperative nodes and making the most use of CMIMO.

Adaptive bit allocation scheme in multi-cell cooperative block diagonalization systems with delayed and limited feedback

In multi-cell cooperative multi-input multi-output （MIMO） systems, base station （BS） can exchange and utilize channel state information （CSI） of adjacent cell users to manage co-channel interference. Users quantize the CSIs of desired channel and interference channels using finite-rate feedback links, then BS can generate cooperative block diagonalization （BD） precoding matrices using the obtained quantized CSI at transmitter to supress co-channel interference. In this paper, a novel adaptive bit allocation scheme is proposed to minimize the rate loss due to imperfect CSI. We derive the closed-form expression of rate loss caused by both channel delay and limited feedback. Based on the derived rate loss expression, the proposed scheme can adaptively allocate more bits to quantize the better channels with smaller delays and fewer bits to worse channels with larger delays. Simulation results show that the proposed scheme yields higher performance than other allocation schemes.