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Tile-based streaming techniques have been widely used to save bandwidth in 360${}^{\circ }$∘ video streaming. However, it is a challenge to determine the right tile size which directly affects the bandwidth usage. Moreover, downloading and processing many small tiles consume a large amount of energy on mobile devices. To solve this problem, we propose to encode the video by taking into account the viewing popularity, where the popularly viewed areas are encoded as macrotiles. We propose techniques for identifying and building macrotiles, and adjusting their sizes to take into account practical issues such as head movement randomness. In some cases, the user's viewing area may not be covered by the constructed macrotiles, and then the conventional tiling scheme is used. To support macrotile based 360${}^{\circ }$∘ video streaming, the client selects the right tiles (a macrotile or a set of conventional tiles) with the right quality level to maximize the QoE under bandwidth constraint. We formulate this problem as an optimization problem which is NP-hard, and then propose a heuristic algorithm to solve it. Through extensive evaluations based on real head movement traces, we demonstrate that the proposed algorithm can significantly improve QoE, save bandwidth usage, and reduce energy consumption.