	Typically minimizing mean square error (e.g., LMS, RLS).
	Least mean squares algorithms (LMS) are less complex, numerically stable but have slower convergence.
	Recursive least squares (RLS) algorithms have faster convergence but have higher complexity, which implies more implementation cost.
	Existing techniques do not achieve both objectives together.
	Novel adaptive filtering techniques are needed to provide low-complexity, fast convergence and good tracking capability to effectively overcome adversities in wireless environment.