Network coding is considered by researchers to be one of the most important areas to apply many of the network applications such as broadcasting and multicasting. In the existing data networks, routers send pockets in the network through store and forward. This way, routers save the pockets in the buffer and send them to the related link or links after finding the pocket route. Through network coding, routers are able to do different mathematical functions on the pockets, for example, they can combine them linearly, and then send them. This has two advantages, including the increase in the network capacity and its robustness. Network coding can reach its maximum capacity, either in its broadcasting or multicasting mood. More over, network coding offers more advantages such as reduction in the energy use, reduction in the amount of delay, reduction in complexity, safety,… . Network coding can also be used in wireless networks. One of the most significant characteristics of wireless networks which distinguishes it from wired networks is the same media in this kind of network. In fact, each forward in the wireless network is a kind of broadcasting. Another feature of wireless network is its faultful links in the network. Coding can reach its optimal throughput besides resisting pocket loss. This study deals with the issue of broadcasting in a wireless network including central station and some receivers. All these receivers are connected to the sender through the same channel. The channel for each receiver is different according to loss rate, dependence and independence. Time is categorized in slots and senders can send only one pocket in each single slot. In broadcasting mood, if a pocket from a sender in each slot includes new information, it is considered as an optimal throughput method. In using network coding in live services, the decoding delay should be lowered. But in general, it is impossible to find a way which has the optimal throughput and the zero amount of decoding delay. So a new coding method is presented whose decoding delay is zero. But we should also calculate the amount of throughput which is lost, using this method. This method has some other advantages such as simplicity, few mathematical functions, and little queue length, which make it a suitable method for live application sensitive to delay. The objective is to see if this optimal throughput can be improved without adding to ARQ complexity. The comparison between the new and the mentioned methods is done through simulation. Keywords: Network Coding, Wireless erasuer networks, Broadcasting, Decoding delay.