In this poster paper we present a data dissemination transmission abstraction for over the air programming (OAP) protocol which is fundamentally different from the previous hop-by-hop transmission protocols. Instead of imposing the greedy requirement that at least one node in the ith hop receives all packets before transmitting packets to the next hop and its neighbours, we take advantage of the spatial diversity and broadcast nature of wireless transmission to adopt a cooperative approach in which node broadcast whatever packets it has received with the expectation that it will recover the lost packets with high probability by overhearing the broadcast transmissions of its neighbours. The use of coded transmissions ensures that this does not lead to the broadcast storm problem. We validate the improved performance our of proposed transmission scheme with respect to the previous state of the art OAP protocols on a proof-of-concept two-hops TelosB wireless sensor network testbed.
While the advantages of multiple-input multiple-output (MIMO) are well known towards improving the network throughput, its adaption for hardware and battery constrained devices such as smartphones and sensor motes is not practical. The use of cooperative communication where nodes share'' their antenna to form a virtual MIMO system, without each node having multiple antennas, has been proposed as a viable technique for such devices @cite_4 . In such cooperative transmission scheme only a small subset of nodes in the networks are source(s) and receiver(s), which relaxes the transmission constraint of delivering @math packets to all nodes of the network as demanded in OAP protocols.
@cite_4
2199681254 2047468088 2139771702 2112490266
This paper explores the usage of cooperative multiple input multiple output (MIMO) technique to minimize energy consumption used to establish communications among distant nodes in a wireless sensor network (WSN). As energy depletion is an outstanding problem in WSN research field, a number of techniques aim to preserve such resource, especially by means of savings during communication among sensor nodes. One such wide used technique is multi-hop communication to diminish the energy required by a single node to transmit a given message, providing a homogeneous consumption of the energy resources among the nodes in the network. However, it is not the case that multi-hop is always more efficient than single-hop, even that it may represent a great depletion of a single node’s energy. In this paper a cooperative MIMO transmission technique for WSN is presented, which is compared to single-hop and multi-hop transmission ones, highlighting its advantages in relation to both. Simulation results support the statement about the utility in applying the proposed technique for energy saving purposes. Large multiple-input multiple-output (MIMO) networks promise high energy efficiency, i.e., much less power is required to achieve the same capacity compared to the conventional MIMO networks if perfect channel state information (CSI) is available at the transmitter. However, in such networks, huge overhead is required to obtain full CSI especially for Frequency-Division Duplex (FDD) systems. To reduce overhead, we propose a downlink antenna selection scheme, which selects S antennas from M > S transmit antennas based on the large scale fading to serve K ≤ S users in large distributed MIMO networks employing regularized zero-forcing (RZF) precoding. In particular, we study the joint optimization of antenna selection, regularization factor, and power allocation to maximize the average weighted sum-rate. This is a mixed combinatorial and non-convex problem whose objective and constraints have no closed-form expressions. We apply random matrix theory to derive asymptotically accurate expressions for the objective and constraints. As such, the joint optimization problem is decomposed into subproblems, each of which is solved by an efficient algorithm. In addition, we derive structural solutions for some special cases and show that the capacity of very large distributed MIMO networks scales as O(KlogM) when M→∞ with K, S fixed. Simulations show that the proposed scheme achieves significant performance gain over various baselines. Recently, the remarkable capacity potential of multiple-input multiple-output (MIMO) wireless communication systems was unveiled. The predicted enormous capacity gain of MIMO is nonetheless significantly limited by cochannel interference (CCI) in realistic cellular environments. The previously proposed advanced receiver technique improves the system performance at the cost of increased receiver complexity, and the achieved system capacity is still significantly away from the interference-free capacity upper bound, especially in environments with strong CCI. In this paper, base station cooperative processing is explored to address the CCI mitigation problem in downlink multicell multiuser MIMO networks, and is shown to dramatically increase the capacity with strong CCI. Both information-theoretic dirty paper coding approach and several more practical joint transmission schemes are studied with pooled and practical per-base power constraints, respectively. Besides the CCI mitigation potential, other advantages of cooperative processing including the power gain, channel rank conditioning advantage, and macrodiversity protection are also addressed. The potential of our proposed joint transmission schemes is verified with both heuristic and realistic cellular MIMO settings. Multiple-input multiple-output (MIMO) is one form of the smart antenna technology that uses multiple antennas at both the transmitter and receiver to improve communication performance. In this paper, we investigate the problem of medium access control in wireless local area networks (WLANs) with downlink multi-user MIMO (DL MU MIMO) capability. We propose a CSMA CA MAC protocol with three response mechanisms for DL MU MIMO and compare the performance of DL MU MIMO with the beam-forming (BF) based approach. A novel per-station weighted queuing mechanism is proposed to mitigate the hidden node problem in the network. Performance analysis and simulation study both show that the proposed DL MU MIMO mechanism incurs low overhead and provides significant throughput performance gain over BF based approach in high SNR scenarios.