Multi-user mmWave MIMO channel estimation with hybrid Beamforming over frequency selective fading channels

In multi-user millimeter wave (mmWave) multiple input multiple output (MIMO) systems, obtaining accurate information/knowledge regarding the channel state is crucial to achieving multi-user interference cancellation and reliable beamforming (BF)-to compensate for severe path loss. This knowledge is nonetheless very challenging to acquire in practice since large antenna arrays experience a low signal-to-noise ratio (SNR) before BF. In this paper, a multi-user channel estimation (CE) scheme namely generalized-block compressed sampling matching pursuit (G-BCoSaMP), is proposed for multi-user mmWave MIMO systems over frequency selective fading channels. This scheme exploits the cluster-structured sparsity in the angular and delay domain of mmWave channels determined by the actual spatial frequencies of each path. As the corresponding spatial frequencies of multi-user mmWave MIMO systems with Hybrid BF often fall between the discrete Fourier transform (DFT) bins due to the continuous Angle of Arrival (AoA)/Angle of Departure (AoD), the proposed G-BCoSaMP algorithm can address the resulting power leakage problem. Simulation results show that the proposed algorithm is effective and offer a better CE performance in terms of MSE when compared to the generalized block orthogonal matching pursuit (G-BOMP) algorithm that does not possess a pruning step

Prolonging lifetime of wireless sensor networks with mobile base station using particle swarm optimization

Wireless sensor networks are a family of networks in wireless communication system and have the potential to become significant subsystem of engineering applications. In view of the fact that the sensor nodes in wireless sensor networks are typically irreplaceable, this type of network should operate with minimum possible energy in order to improve overall energy efficiency. Therefore, the protocols and algorithms developed for sensor networks must incorporate energy consumption as the highest priority optimization goal. Since the base station in sensor networks is usually a node with high processing power, high storage capacity and the battery used can be rechargeable, the base station can be utilized to collect data from each sensor node in the sensing area by moving closer to the transmitting node. In this paper, we proposed an energy-efficient protocol for the movement of mobile base station using particle swarm optimization (PSO) method in wireless sensor networks. Simulation results demonstrate that the proposed protocol can improve the network lifetime, data delivery and energy consumption compared to existing energy-efficient protocols developed for this network

Compressed channel estimation for massive MIMO-OFDM systems over doubly selective channels

Doubly selective (DS) channel estimation for the downlink massive multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is a challenging problem, due to the requirements on high pilots overhead and prohibitive complexity. In this paper, by exploiting the highly correlated spatial structure of the obtained array response vectors and sparsity of the multipath signal components of the massive MIMO-OFDM channels, a modified spatial basis expansion model (modified-SBEM) is introduced. Thus, using complex exponential (CE-) modified-SBEM (i.e., modified CE-SBEM) can improve the resolution of the angles of departures (AoDs) information to represent the downlink with far fewer parameter dimensions, since the AoDs are much slower than path gains. Subsequently, we jointly design the effective pilot power and pilot placement for sparse channel estimation by means of an extended model. Our design is based on the block-coherence and sub-coherence simultaneous minimization of the measurement matrix associated with the massive MIMO-OFDM system pilot subcarriers. Furthermore, we leverage the sparse nature of the massive MIMO-OFDM system to formulate the quantized AoDs estimation into a block-sparse signal recovery problem, where the measurement matrix is designed based on the estimated virtual AoD. Thus, a new algorithm namely, generalized quasi-block simultaneous orthogonal matching pursuit (gQBSO), is introduced to solve the problem by providing sparse signal reconstruction solution. Simulation results demonstrate that the proposed scheme can effectively estimate the DS channel for massive MIMO-OFDM systems compared with other existing algorithms. For example, at SNR=20 dB for K=4 users, Doppler shift=0.093 with NT=32 antenna size, the adaptive-QBSO algorithm with G-SBEM and the proposed gQBSO with modified-SBEM can realize approximately 75.44%and 85.14% of the NMSE achieved by the oracle estimator with modified-SBEM

On the spectral-efficiency of low-complexity and resolution hybrid precoding and combining transceivers for mmWave MIMO systems

Millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems will almost certainly use hybrid precoding to realize beamforming with few numbers of RF chains to reduce energy consumption, but require low complexity technique to improve spectral efficiency. While energy-efficient hybrid analog/digital precoders and combiners designs can subdue the high pathloss inherent in mmWave channels, they assume the use of infinite- (or high-) resolution phase shifters to realize the analog precoder and combiner pair which results in high hardware cost and power consumption. One promising solution is to employ the use of low-resolution phase shifters. In this paper, we first diverse the exploration of multiple candidates of array response vectors, to propose low-complexity hybrid precoder and combiner (LcHPC) design via stage-determined matching pursuit (SdMP) namely, LcHPC-SdMP for pursuing better achievable rate for mmWave MIMO systems. We initially decouple the joint optimization over hybrid precoders and combiners into two separate sparse recovery problems. Specifically, LcHPC-SdMP algorithm revises the identification step of orthogonal matching pursuit (OMP) to the selection of multiple "correct" column indices of the matrix of array response vectors, per iteration. Then adds a pruning step-after satisfying a sparsity level condition, to iteratively refine the sparse solution which aids in further accelerating the algorithm, by requiring fewer iterations. We then propose an algorithm which iteratively designs low-resolution (two-bit) hybrid analog-digital precoder and combiner (LrHPC), for pursuing efficiency while maximizing spectral efficiency. Simulation results demonstrate that the proposed LcHPC-SdMP algorithm performs very close to its full-digital precoding and achieves better spectral efficiency over state-of-the-art algorithms with a substantially reduced number of iteration than the recently proposed schemes. In addition, simulation results also reveal that the achievable rate of the proposed LrHPC algorithm is higher than those of the existing algorithms under consideration

Adaptive transport layer protocol for highly dynamic environment

Computer and wireless communication require Internet accessibility at anytime and anywhere; this includes in a high-speed mobile station such as in speedy trains, fast moving cars as vehicle-to-infrastructure communication. However, wireless Quality of Service (QoS) provisioning in such an environment is more challenging. This increased the development of numerous schemes concerning the need of smooth handover of the mobile nodes. Conversely, transport layer (L4 in ISO layers) protocols such as stream control transmission protocol can support such a seamless handover in high-speed mobility users. This article highlights on the issues of moving users in mobile WiMAX networks. An adaptation of transport layer protocol of the high mobility vehicle that supports seamless handover can guarantee and maintain QoS for rapid handover rates. The results show an improvement of L4 protocol in terms of delay time and throughput in order to enable efficient and robust mobility aware protocols

Power consumption efficient routing protocol for forest fire detection based on mobile sensor networks

Wireless sensor networks play an important role in many applications that require networks that could be used in emergency and rescue operations or in disasters such as forest fire. Forest fires are costing millions of dollars in addition to the big losses of trees and air pollution that is spreading to the neighbouring countries. In such disaster, an effective and reliable routing protocol in terms of energy consumption is much needed for continuous monitoring. This paper presents a new routing protocol named Power Consumption Efficient-Optimized Link State Routing (PCE-OLSR) protocol in the forest fire detection. PCE-OLSR protocol exploits the energy of the nodes that is located in the fire zone in order to fully utilize its energy and consequently preserved the energy of other nodes in the network. The proposed PCE-OLSR protocol has been evaluated and compared with the traditional OLSR protocol in terms of packet delivery ratio, end to end delay, energy consumption and routing overhead. Results have shown that PCE-OLSR performs better than its comparative

Multi hop transmission in IEEE 802.11 low rate ad hoc network using ARP-route

Ad hoc networks are becoming more important in the modern complex environment. The ad hoc network can be used to instantly connect to the local or remote networks such as the Internet without the need of pre-existing infrastructure or centralized administration. The users of the network together will establish the infrastructure. The disadvantage of wireless communication is that it has limited range of radio transmission. Due to this, multiple network ‘hops’ are needed for one device to exchange data with another device across the network. In an ad hoc network, these devices will not only operate as a host but also as a router to forward the packets. There are varieties of routing protocols targeted for this environment that have been proposed and developed. However, most of them suffer from high overhead data traffic. The main purpose of this project is to implement the ad hoc network with the existing network protocol that had already been used in network environment which is the Address Resolution Protocol (ARP). ARP was designed to announce or find MAC addresses. The novelty of this study is that we have extended the usage of the ARP protocol to act as routing protocol in wireless ad hoc network. The ARP route provides two new operation types, ARP Forward Request and ARP Forward Reply to allow the multihop transmission using intermediate nodes to forward the request and reply. These two operation types only used the current operation codes which are ‘0x0001’ for request and ‘0x0002’ for reply. This work on the routing protocol creates a new operation code for the ARP forwarding scheme which is ‘0x000c’ for forwarding. We have successfully managed to create a multi hop transmission in an ad hoc network by using the current existing operation code for the ARP forwarding. The work scope focus only on proving that the method can be applied hence it is not necessarily to prove the effectiveness of this proposed method yet. Therefore, the outcome of the study shows that the data can be sent through multi hop transmission until it reaches the destination. The 802.11b test-bed has been configured and the ARP routing protocol has been implemented for multi hop transmission. The experiment in the open space provides the comparison of environment with obstacles and without obstacles. We manage to get more than 50% of packet receive at a place with no obstacles and more than 45% in a place with obstacles. The proof of method is shown by using several graphs namely in terms of time, packet loss and also throughput