In　a　mobile　network,　wireless　data　broadcast　over　m　channels　(frequencies)　is　a　powerful　means　for　distributed　dissemination　of　data　to　clients　who　access　the　channels　through　multi-antennae　equipped　on　their　mobile　devices.　The　δ　-antennae　largest　weight　data　retrieval　(δ　ALWDR)　problem　is　to　compute　a　schedule　for　downloading　a　subset　of　data　items　that　has　a　maximum　total　weight　using　δ　antennae　in　a　given　time　interval.　In　this　paper,　we　first　give　a　linear　programming　(LP)　relaxation　for　δ　ALWDR　and　show　that　it　is　polynomial-time　solvable　when　every　data　item　appears　at　most　once.　We　also　show　that　when　there　exist　data　items　with　multiple　occurrences,　the　integrality　gap　of　this　LP　formula　is　2.　We　then　present　an　approximation　algorithm　of　ratio　1-1/e　for　the　δ-antennae　γ　-separated　largest　weight　data　retrieval　(δ　A　γ　LWDR)　problem,　a　weaker　version　of　δ　ALWDR　where　each　block　of　up　to　γ　data　(time)　slots　is　separated　by　a　vacant　slot　on　all　channels,　applying　the　techniques　called　collectively　randomized　LP　rounding　and　layered　DAG　construction.　We　show　that　δ　A　γ　LWDR　is　NP-　complete　even　for　the　simple　case　of　γ　=2　,　m=3　,　and　equal-weight　data　items　each　appearing　up　to　3　times.　Our　algorithm　runs　in　time　O(2γm7T3.5L)　,　where　T　is　the　number　of　time　slots,　and　L　is　the　maximum　length　of　the　input.　Then,　from　the　simple　observation　that　a　ratio　α　approximation　solution　to　δ　A　γ　LWDR　implies　a　ratio　α-　approximation　solution　to　δ　ALWDR　for　any　fixed　＞0,　we　immediately　have　an　approximation　algorithm　of　ratio　1-1/e-　for　δ　ALWDR.　Our　algorithm　has　the　same　approximation　ratio　as　the　known　result　in　[15]　which　holds　only　for　δ　=1　,　with　a　significantly　lower　time　complexity　of　O(211/m7T3.5L)　(improved　from　O(3.5m3.5/T3.5L)　of　[15]　).　As　a　by-product,　we　also　give　a　fixed-parameter　tractable　(fpt-)algorithm　of　time　complexity　O(2Bm7T3.5L)for　δ　ALWDR,　where　B　is　the　number　of　time　slots　that　contain　data　items　with　multiple　occurrences.　©　2002-2012　IEEE.