This paper studies the downlink beamforming for a multi-cell system, where multiple base stations (BSs) each with multiple antennas cooperatively design their respective transmit beamforming vectors. It is assumed that all mobile stations (MSs) are equipped with a single antenna each, and there is one active MS in each cell at one time. Accordingly, the system of interest can be modeled by a multiple-input single-output (MISO) Gaussian interference channel (IC), termed as MISO-IC, with interference treated as additive Gaussian noise. We are interested in designing a multi-cell cooperative downlink beamforming scheme to achieve different rate-tuples for active MSs on the Pareto boundary of the achievable rate region for the MISO-IC, which is in general a non-convex problem due to the coupled signal structure. By exploring the relationship between the MISO-IC and the cognitive radio (CR) MISO channel, we show that each Pareto-boundary rate-tuple of the MISO-IC can be achieved when each of the MSs attains its own channel capacity subject to a certain set of interference-power constraints (also known as interference-temperature constraints in the CR system) at the other MS receivers. Furthermore, we show that this result leads to a decentralized algorithm for implementing the multi-cell cooperative downlink beamforming, where all different pairs of BSs independently search for their mutually desirable interference-temperature constraints, under which their respective beamforming vectors are optimized to maximize the individual transmit rates.